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files changed, 94 insertions(+), 3 deletions(-) diff --git a/src/ontogpt/engines/generic_engine.py b/src/ontogpt/engines/generic_engine.py index 85eef7d49..a6f705db2 100644 --- a/src/ontogpt/engines/generic_engine.py +++ b/src/ontogpt/engines/generic_engine.py @@ -1,4 +1,29 @@ -"""Generic LLM interface engine.""" +"""Generic LLM interface engine. + +This module defines a generic engine for interfacing with +a large language model (LLM) to answer questions based on +provided templates and instructions. + +Classes: + Question: A Pydantic model representing a question + with various attributes. + Instruction: A Pydantic model representing an instruction + with a name, text, and template. + QuestionCollection: A Pydantic model representing a + collection of questions and instructions. + GenericEngine: A dataclass inheriting from KnowledgeEngine, + responsible for running the engine to process questions and + generate answers. + +Constants: + MAX_TOKENS: The maximum number of tokens to be generated by the LLM. + +Methods: + GenericEngine.run: Processes a collection of questions using + provided templates and instructions, and yields questions with + generated answers. + +""" import logging from copy import deepcopy diff --git a/src/ontogpt/engines/knowledge_engine.py b/src/ontogpt/engines/knowledge_engine.py index 40ae76801..d7b1c79ee 100644 --- a/src/ontogpt/engines/knowledge_engine.py +++ b/src/ontogpt/engines/knowledge_engine.py @@ -1,4 +1,70 @@ -"""Main Knowledge Extractor class.""" +"""Main Knowledge Extractor class. + +This module defines the KnowledgeEngine class, an +abstract base class for extracting knowledge from +text using knowledge sources and language models. +It includes methods for chunking text, extracting +annotations from text and files, loading dictionaries, +synthesizing and generalizing extraction results, +mapping terms, and normalizing named entities. + +Classes: + KnowledgeEngine: Abstract base class for all knowledge engines. + +Functions: + chunk_text_by_sentence(text: str, window_size=3) -> Iterator[str]: + Chunk text into windows of sentences. + + chunk_text_by_char(text: str, window_size=1000) -> Iterator[str]: + Chunk text into windows of characters. + + set_api_key(key: str): + Set the API key for accessing external language model. + + extract_from_text(text: str, cls: ClassDefinition = None, object: OBJECT = None) -> ExtractionResult: + Abstract method to extract knowledge from text. + + extract_from_file(file: Union[str, Path, TextIO]) -> pydantic.BaseModel: + Extract annotations from the given text file. + + load_dictionary(path: Union[str, Path, list]): + Load a dictionary from a given path or list. + + synthesize(cls: ClassDefinition = None, object: OBJECT = None) -> ExtractionResult: + Abstract method to synthesize extraction results. + + generalize(object: Union[pydantic.BaseModel, dict], examples: List[EXAMPLE], show_prompt: bool) -> ExtractionResult: + Abstract method to generalize extraction results. + + map_terms(terms: List[str], ontology: str, show_prompt: bool) -> Dict[str, str]: + Abstract method to map terms to ontology. + + _get_openai_api_key(): + Get the OpenAI API key from the environment. + + get_annotators(cls: ClassDefinition = None) -> List[BasicOntologyInterface]: + + promptable_slots(cls: Optional[ClassDefinition] = None) -> List[SlotDefinition]: + + slot_is_skipped(slot: SlotDefinition) -> bool: + Check if a slot is skipped for prompting. + + normalize_named_entity(text: str, range: ElementName) -> str: + Ground and normalize named entities to preferred ID prefixes. + + is_valid_identifier(input_id: str, cls: ClassDefinition) -> bool: + Check if an identifier is valid for a given class. + + normalize_identifier(input_id: str, cls: ClassDefinition) -> Iterator[str]: + + map_identifier(input_id: str, cls: ClassDefinition) -> Iterator[str]: + Map an identifier to a preferred prefix. + + groundings(text: str, cls: ClassDefinition) -> Iterator[str]: + + merge_resultsets(resultset: List[ExtractionResult], unique_fields: List[str]) -> ExtractionResult: + +""" import logging import re diff --git a/src/ontogpt/engines/spires_engine.py b/src/ontogpt/engines/spires_engine.py index bd1c50f5b..e47196d76 100644 --- a/src/ontogpt/engines/spires_engine.py +++ b/src/ontogpt/engines/spires_engine.py @@ -1,5 +1,5 @@ """ -Main Knowledge Extractor class. +Main SPIRES Knowledge Extractor class. This works by recursively constructing structured prompt-completions where a pseudo-YAML structure is requested, where the YAML From 12886fc027c0b80b24b6bcbb1c10556f0f910b92 Mon Sep 17 00:00:00 2001 From: caufieldjh Date: Fri, 8 Nov 2024 14:32:54 -0500 Subject: [PATCH 3/7] Docstring for extractor functions --- src/ontogpt/ontex/extractor.py | 49 +++++++++++++++++++++++++++++++++- 1 file changed, 48 insertions(+), 1 deletion(-) diff --git a/src/ontogpt/ontex/extractor.py b/src/ontogpt/ontex/extractor.py index eb5644865..002d3054b 100644 --- a/src/ontogpt/ontex/extractor.py +++ b/src/ontogpt/ontex/extractor.py @@ -1,4 +1,51 @@ -"""Tools to extract sub-ontologies and reasoner tasks.""" +"""Tools to extract sub-ontologies and reasoner tasks. + +This module provides classes and functions to extract sub-ontologies and reasoner tasks from a given ontology. +These tasks can be used to query or evaluate the ontology using a ReasonerEngine object. + +Classes: + Axiom: Represents an individual logical axiom. + Ontology: Represents a collection of axioms. + Query: Represents a query. + Explanation: Represents a set of axioms that entail some explained axiom. + Answer: Represents an individual answer to a query. + ObjectAnswer: Represents an answer that is an object, e.g., class. + ClassAnswer: Represents an answer that is an OWL class. + InstanceAnswer: Represents an answer that is an OWL individual. + BooleanAnswer: Represents an answer that is a boolean, e.g., true or false. + AxiomAnswer: Represents an answer that is an axiom. + ExampleQueryAnswers: Represents an example query plus all expected answers. + Example: Represents an example of a query plus answers in the context of an ontology. + LLMReasonMethodType: Enum representing different reasoning method types. + Task: Represents a task which is a query on an ontology that has a set of defined answers. + OntologyCoherencyTask: Represents a task to determine if an ontology is coherent. + EntailedIndirectSuperClassTask: Represents a task to determine the indirect superclasses of a class. + EntailedTransitiveSuperClassTask: Represents a task to determine all transitive superclasses of a class. + EntailedSubClassOfExpressionTask: Represents a task to determine the subclasses of a class expression. + EntailedDirectSuperClassTask: Represents a task to determine the direct superclasses of a class. + MostRecentCommonSubsumerTask: Represents a task to determine the most specific common ancestors. + TaxonConstraintTask: Represents a task to determine inapplicable classes by taxon. + ABoxTask: Represents a task to infer assertions over property chains and transitivity in aboxes. + TaskCollection: Represents a collection of tasks. + OntologyExtractor: Extracts Task objects from an ontology. + +Functions: + TaskCollection.load(file_or_object): Loads a TaskCollection from a file or object. + OntologyExtractor.create_task(task_type, parameters, **kwargs): Creates a task of the specified type. + OntologyExtractor.create_random_tasks(num_tasks_per_type, methods, abox): Creates random tasks. + OntologyExtractor.extract_ontology(terms, roots, predicates, include_abox): Extracts an ontology module. + OntologyExtractor.extract_indirect_superclasses_task(subclass, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all indirect superclasses of a class. + OntologyExtractor.extract_transitive_superclasses_task(subclass, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all transitive superclasses of a class. + OntologyExtractor.extract_abox_task(subject, siblings, predicate, select_random, **kwargs): Extracts a task for finding all entailed edges. + OntologyExtractor.extract_most_recent_common_subsumers_task(subclass1, subclass2, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all MRCAs of a pair of classes. + OntologyExtractor.extract_subclass_of_expression_task(superclass, predicate, siblings, predicates, select_random, **kwargs): Extracts a task for finding all subclasses of a class expression. + OntologyExtractor.extract_incoherent_ontology_task(incoherents, siblings, disjoints, spiked_relationships, roots, select_random, **kwargs): Extracts a task for testing ability to find incoherencies based on disjointness axioms. + OntologyExtractor.extract_taxon_constraint_task(term, taxon, siblings, never_in, select_random, **kwargs): Extracts a task for evaluating taxon constraints. + OntologyExtractor._axiom(rel, tbox): Creates an axiom from a relationship. + OntologyExtractor._name(curie): Returns the name of a CURIE. + OntologyExtractor.extract_rbox(): Extracts RBox axioms. + +""" import base64 import logging From 5124d4ebe393b3a373c1401fdd6a80397a64de9c Mon Sep 17 00:00:00 2001 From: caufieldjh Date: Fri, 8 Nov 2024 14:39:20 -0500 Subject: [PATCH 4/7] Bump version to 1.0.7 --- pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index f7a0bb74e..869fa0469 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "ontogpt" -version = "1.0.6" +version = "1.0.7" description = "OntoGPT" authors = ["Chris Mungall ", "J. Harry Caufield "] license = "BSD-3" From bac365bdc1d30325b5d03e4074585d27f005b76c Mon Sep 17 00:00:00 2001 From: caufieldjh Date: Fri, 8 Nov 2024 14:47:36 -0500 Subject: [PATCH 5/7] Linting --- src/ontogpt/engines/knowledge_engine.py | 9 +- src/ontogpt/ontex/extractor.py | 48 ++-- src/ontogpt/templates/personinfo.py | 281 ++++++++++++++++++++++++ src/ontogpt/templates/personinfo.yaml | 42 ++++ 4 files changed, 361 insertions(+), 19 deletions(-) create mode 100644 src/ontogpt/templates/personinfo.py create mode 100644 src/ontogpt/templates/personinfo.yaml diff --git a/src/ontogpt/engines/knowledge_engine.py b/src/ontogpt/engines/knowledge_engine.py index d7b1c79ee..a7c88f4a7 100644 --- a/src/ontogpt/engines/knowledge_engine.py +++ b/src/ontogpt/engines/knowledge_engine.py @@ -21,7 +21,8 @@ set_api_key(key: str): Set the API key for accessing external language model. - extract_from_text(text: str, cls: ClassDefinition = None, object: OBJECT = None) -> ExtractionResult: + extract_from_text(text: str, cls: ClassDefinition = None, + object: OBJECT = None) -> ExtractionResult: Abstract method to extract knowledge from text. extract_from_file(file: Union[str, Path, TextIO]) -> pydantic.BaseModel: @@ -33,7 +34,8 @@ synthesize(cls: ClassDefinition = None, object: OBJECT = None) -> ExtractionResult: Abstract method to synthesize extraction results. - generalize(object: Union[pydantic.BaseModel, dict], examples: List[EXAMPLE], show_prompt: bool) -> ExtractionResult: + generalize(object: Union[pydantic.BaseModel, dict], + examples: List[EXAMPLE], show_prompt: bool) -> ExtractionResult: Abstract method to generalize extraction results. map_terms(terms: List[str], ontology: str, show_prompt: bool) -> Dict[str, str]: @@ -62,7 +64,8 @@ groundings(text: str, cls: ClassDefinition) -> Iterator[str]: - merge_resultsets(resultset: List[ExtractionResult], unique_fields: List[str]) -> ExtractionResult: + merge_resultsets(resultset: List[ExtractionResult], + unique_fields: List[str]) -> ExtractionResult: """ diff --git a/src/ontogpt/ontex/extractor.py b/src/ontogpt/ontex/extractor.py index 002d3054b..6faf1fec9 100644 --- a/src/ontogpt/ontex/extractor.py +++ b/src/ontogpt/ontex/extractor.py @@ -1,7 +1,8 @@ """Tools to extract sub-ontologies and reasoner tasks. -This module provides classes and functions to extract sub-ontologies and reasoner tasks from a given ontology. -These tasks can be used to query or evaluate the ontology using a ReasonerEngine object. +This module provides classes and functions to extract sub-ontologies and reasoner tasks from a +given ontology. These tasks can be used to query or evaluate the ontology using a ReasonerEngine +object. Classes: Axiom: Represents an individual logical axiom. @@ -19,32 +20,47 @@ LLMReasonMethodType: Enum representing different reasoning method types. Task: Represents a task which is a query on an ontology that has a set of defined answers. OntologyCoherencyTask: Represents a task to determine if an ontology is coherent. - EntailedIndirectSuperClassTask: Represents a task to determine the indirect superclasses of a class. - EntailedTransitiveSuperClassTask: Represents a task to determine all transitive superclasses of a class. - EntailedSubClassOfExpressionTask: Represents a task to determine the subclasses of a class expression. + EntailedIndirectSuperClassTask: Represents a task to determine the indirect superclasses of a + class. + EntailedTransitiveSuperClassTask: Represents a task to determine all transitive superclasses of + a class. + EntailedSubClassOfExpressionTask: Represents a task to determine the subclasses of a class + expression. EntailedDirectSuperClassTask: Represents a task to determine the direct superclasses of a class. MostRecentCommonSubsumerTask: Represents a task to determine the most specific common ancestors. TaxonConstraintTask: Represents a task to determine inapplicable classes by taxon. - ABoxTask: Represents a task to infer assertions over property chains and transitivity in aboxes. + ABoxTask: Represents a task to infer assertions over property chains and transitivity in + aboxes. TaskCollection: Represents a collection of tasks. OntologyExtractor: Extracts Task objects from an ontology. Functions: TaskCollection.load(file_or_object): Loads a TaskCollection from a file or object. - OntologyExtractor.create_task(task_type, parameters, **kwargs): Creates a task of the specified type. + OntologyExtractor.create_task(task_type, parameters, **kwargs): Creates a task of the specified + type. OntologyExtractor.create_random_tasks(num_tasks_per_type, methods, abox): Creates random tasks. - OntologyExtractor.extract_ontology(terms, roots, predicates, include_abox): Extracts an ontology module. - OntologyExtractor.extract_indirect_superclasses_task(subclass, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all indirect superclasses of a class. - OntologyExtractor.extract_transitive_superclasses_task(subclass, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all transitive superclasses of a class. - OntologyExtractor.extract_abox_task(subject, siblings, predicate, select_random, **kwargs): Extracts a task for finding all entailed edges. - OntologyExtractor.extract_most_recent_common_subsumers_task(subclass1, subclass2, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all MRCAs of a pair of classes. - OntologyExtractor.extract_subclass_of_expression_task(superclass, predicate, siblings, predicates, select_random, **kwargs): Extracts a task for finding all subclasses of a class expression. - OntologyExtractor.extract_incoherent_ontology_task(incoherents, siblings, disjoints, spiked_relationships, roots, select_random, **kwargs): Extracts a task for testing ability to find incoherencies based on disjointness axioms. - OntologyExtractor.extract_taxon_constraint_task(term, taxon, siblings, never_in, select_random, **kwargs): Extracts a task for evaluating taxon constraints. + OntologyExtractor.extract_ontology(terms, roots, predicates, include_abox): Extracts an ontology + module. + OntologyExtractor.extract_indirect_superclasses_task(subclass, siblings, roots, predicates, + select_random, **kwargs): Extracts a task for finding all indirect superclasses of a class. + OntologyExtractor.extract_transitive_superclasses_task(subclass, siblings, roots, predicates, + select_random, **kwargs): Extracts a task for finding all transitive superclasses of a class. + OntologyExtractor.extract_abox_task(subject, siblings, predicate, select_random, **kwargs): + Extracts a task for finding all entailed edges. + OntologyExtractor.extract_most_recent_common_subsumers_task(subclass1, subclass2, siblings, + roots, predicates, select_random, **kwargs): Extracts a task for finding all MRCAs of a pair + of classes. + OntologyExtractor.extract_subclass_of_expression_task(superclass, predicate, siblings, + predicates, select_random, **kwargs): Extracts a task for finding all subclasses of a class + expression. + OntologyExtractor.extract_incoherent_ontology_task(incoherents, siblings, disjoints, + spiked_relationships, roots, select_random, **kwargs): Extracts a task for testing ability + to find incoherencies based on disjointness axioms. + OntologyExtractor.extract_taxon_constraint_task(term, taxon, siblings, never_in, select_random, + **kwargs): Extracts a task for evaluating taxon constraints. OntologyExtractor._axiom(rel, tbox): Creates an axiom from a relationship. OntologyExtractor._name(curie): Returns the name of a CURIE. OntologyExtractor.extract_rbox(): Extracts RBox axioms. - """ import base64 diff --git a/src/ontogpt/templates/personinfo.py b/src/ontogpt/templates/personinfo.py new file mode 100644 index 000000000..e27e544c8 --- /dev/null +++ b/src/ontogpt/templates/personinfo.py @@ -0,0 +1,281 @@ +from __future__ import annotations + +import re +import sys +from datetime import ( + date, + datetime, + time +) +from decimal import Decimal +from enum import Enum +from typing import ( + Any, + ClassVar, + Dict, + List, + Literal, + Optional, + Union +) + +from pydantic import ( + BaseModel, + ConfigDict, + Field, + RootModel, + field_validator +) + + +metamodel_version = "None" +version = "None" + + +class ConfiguredBaseModel(BaseModel): + model_config = ConfigDict( + validate_assignment = True, + validate_default = True, + extra = "forbid", + arbitrary_types_allowed = True, + use_enum_values = True, + strict = False, + ) + pass + + + + +class LinkMLMeta(RootModel): + root: Dict[str, Any] = {} + model_config = ConfigDict(frozen=True) + + def __getattr__(self, key:str): + return getattr(self.root, key) + + def __getitem__(self, key:str): + return self.root[key] + + def __setitem__(self, key:str, value): + self.root[key] = value + + def __contains__(self, key:str) -> bool: + return key in self.root + + +linkml_meta = LinkMLMeta({'default_prefix': 'personinfo', + 'default_range': 'string', + 'id': 'https://w3id.org/linkml/examples/personinfo', + 'imports': ['linkml:types', 'core'], + 'name': 'personinfo', + 'prefixes': {'linkml': {'prefix_prefix': 'linkml', + 'prefix_reference': 'https://w3id.org/linkml/'}, + 'personinfo': {'prefix_prefix': 'personinfo', + 'prefix_reference': 'https://w3id.org/linkml/examples/personinfo/'}}, + 'source_file': '/home/harry/ontogpt/src/ontogpt/templates/personinfo.yaml'} ) + +class NullDataOptions(str, Enum): + UNSPECIFIED_METHOD_OF_ADMINISTRATION = "UNSPECIFIED_METHOD_OF_ADMINISTRATION" + NOT_APPLICABLE = "NOT_APPLICABLE" + NOT_MENTIONED = "NOT_MENTIONED" + + + +class ExtractionResult(ConfiguredBaseModel): + """ + A result of extracting knowledge on text + """ + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'http://w3id.org/ontogpt/core'}) + + input_id: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'input_id', 'domain_of': ['ExtractionResult']} }) + input_title: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'input_title', 'domain_of': ['ExtractionResult']} }) + input_text: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'input_text', 'domain_of': ['ExtractionResult']} }) + raw_completion_output: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'raw_completion_output', 'domain_of': ['ExtractionResult']} }) + prompt: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'prompt', 'domain_of': ['ExtractionResult']} }) + extracted_object: Optional[Any] = Field(None, description="""The complex objects extracted from the text""", json_schema_extra = { "linkml_meta": {'alias': 'extracted_object', 'domain_of': ['ExtractionResult']} }) + named_entities: Optional[List[Any]] = Field(None, description="""Named entities extracted from the text""", json_schema_extra = { "linkml_meta": {'alias': 'named_entities', 'domain_of': ['ExtractionResult']} }) + + +class NamedEntity(ConfiguredBaseModel): + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'abstract': True, 'from_schema': 'http://w3id.org/ontogpt/core'}) + + id: str = Field(..., description="""A unique identifier for the named entity""", json_schema_extra = { "linkml_meta": {'alias': 'id', + 'annotations': {'prompt.skip': {'tag': 'prompt.skip', 'value': 'true'}}, + 'comments': ['this is populated during the grounding and normalization step'], + 'domain_of': ['NamedEntity', 'Publication', 'Person']} }) + label: Optional[str] = Field(None, description="""The label (name) of the named thing""", json_schema_extra = { "linkml_meta": {'alias': 'label', + 'aliases': ['name'], + 'annotations': {'owl': {'tag': 'owl', + 'value': 'AnnotationProperty, AnnotationAssertion'}}, + 'domain_of': ['NamedEntity'], + 'slot_uri': 'rdfs:label'} }) + original_spans: Optional[List[str]] = Field(None, description="""The coordinates of the original text span from which the named entity was extracted, inclusive. For example, \"10:25\" means the span starting from the 10th character and ending with the 25th character. The first character in the text has index 0. Newlines are treated as single characters. Multivalued as there may be multiple spans for a single text.""", json_schema_extra = { "linkml_meta": {'alias': 'original_spans', + 'annotations': {'prompt.skip': {'tag': 'prompt.skip', 'value': 'true'}}, + 'comments': ['This is determined during grounding and normalization', + 'But is based on the full input text'], + 'domain_of': ['NamedEntity']} }) + + @field_validator('original_spans') + def pattern_original_spans(cls, v): + pattern=re.compile(r"^\d+:\d+$") + if isinstance(v,list): + for element in v: + if isinstance(v, str) and not pattern.match(element): + raise ValueError(f"Invalid original_spans format: {element}") + elif isinstance(v,str): + if not pattern.match(v): + raise ValueError(f"Invalid original_spans format: {v}") + return v + + +class CompoundExpression(ConfiguredBaseModel): + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'abstract': True, 'from_schema': 'http://w3id.org/ontogpt/core'}) + + pass + + +class Triple(CompoundExpression): + """ + Abstract parent for Relation Extraction tasks + """ + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'abstract': True, 'from_schema': 'http://w3id.org/ontogpt/core'}) + + subject: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'subject', 'domain_of': ['Triple']} }) + predicate: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'predicate', 'domain_of': ['Triple']} }) + object: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'object', 'domain_of': ['Triple']} }) + qualifier: Optional[str] = Field(None, description="""A qualifier for the statements, e.g. \"NOT\" for negation""", json_schema_extra = { "linkml_meta": {'alias': 'qualifier', 'domain_of': ['Triple']} }) + subject_qualifier: Optional[str] = Field(None, description="""An optional qualifier or modifier for the subject of the statement, e.g. \"high dose\" or \"intravenously administered\"""", json_schema_extra = { "linkml_meta": {'alias': 'subject_qualifier', 'domain_of': ['Triple']} }) + object_qualifier: Optional[str] = Field(None, description="""An optional qualifier or modifier for the object of the statement, e.g. \"severe\" or \"with additional complications\"""", json_schema_extra = { "linkml_meta": {'alias': 'object_qualifier', 'domain_of': ['Triple']} }) + + +class TextWithTriples(ConfiguredBaseModel): + """ + A text containing one or more relations of the Triple type. + """ + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'http://w3id.org/ontogpt/core'}) + + publication: Optional[Publication] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'publication', + 'annotations': {'prompt.skip': {'tag': 'prompt.skip', 'value': 'true'}}, + 'domain_of': ['TextWithTriples', 'TextWithEntity']} }) + triples: Optional[List[Triple]] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'triples', 'domain_of': ['TextWithTriples']} }) + + +class TextWithEntity(ConfiguredBaseModel): + """ + A text containing one or more instances of a single type of entity. + """ + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'http://w3id.org/ontogpt/core'}) + + publication: Optional[Publication] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'publication', + 'annotations': {'prompt.skip': {'tag': 'prompt.skip', 'value': 'true'}}, + 'domain_of': ['TextWithTriples', 'TextWithEntity']} }) + entities: Optional[List[str]] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'entities', 'domain_of': ['TextWithEntity']} }) + + +class RelationshipType(NamedEntity): + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'http://w3id.org/ontogpt/core', + 'id_prefixes': ['RO', 'biolink']}) + + id: str = Field(..., description="""A unique identifier for the named entity""", json_schema_extra = { "linkml_meta": {'alias': 'id', + 'annotations': {'prompt.skip': {'tag': 'prompt.skip', 'value': 'true'}}, + 'comments': ['this is populated during the grounding and normalization step'], + 'domain_of': ['NamedEntity', 'Publication', 'Person']} }) + label: Optional[str] = Field(None, description="""The label (name) of the named thing""", json_schema_extra = { "linkml_meta": {'alias': 'label', + 'aliases': ['name'], + 'annotations': {'owl': {'tag': 'owl', + 'value': 'AnnotationProperty, AnnotationAssertion'}}, + 'domain_of': ['NamedEntity'], + 'slot_uri': 'rdfs:label'} }) + original_spans: Optional[List[str]] = Field(None, description="""The coordinates of the original text span from which the named entity was extracted, inclusive. For example, \"10:25\" means the span starting from the 10th character and ending with the 25th character. The first character in the text has index 0. Newlines are treated as single characters. Multivalued as there may be multiple spans for a single text.""", json_schema_extra = { "linkml_meta": {'alias': 'original_spans', + 'annotations': {'prompt.skip': {'tag': 'prompt.skip', 'value': 'true'}}, + 'comments': ['This is determined during grounding and normalization', + 'But is based on the full input text'], + 'domain_of': ['NamedEntity']} }) + + @field_validator('original_spans') + def pattern_original_spans(cls, v): + pattern=re.compile(r"^\d+:\d+$") + if isinstance(v,list): + for element in v: + if isinstance(v, str) and not pattern.match(element): + raise ValueError(f"Invalid original_spans format: {element}") + elif isinstance(v,str): + if not pattern.match(v): + raise ValueError(f"Invalid original_spans format: {v}") + return v + + +class Publication(ConfiguredBaseModel): + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'http://w3id.org/ontogpt/core'}) + + id: Optional[str] = Field(None, description="""The publication identifier""", json_schema_extra = { "linkml_meta": {'alias': 'id', 'domain_of': ['NamedEntity', 'Publication', 'Person']} }) + title: Optional[str] = Field(None, description="""The title of the publication""", json_schema_extra = { "linkml_meta": {'alias': 'title', 'domain_of': ['Publication']} }) + abstract: Optional[str] = Field(None, description="""The abstract of the publication""", json_schema_extra = { "linkml_meta": {'alias': 'abstract', 'domain_of': ['Publication']} }) + combined_text: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'combined_text', 'domain_of': ['Publication']} }) + full_text: Optional[str] = Field(None, description="""The full text of the publication""", json_schema_extra = { "linkml_meta": {'alias': 'full_text', 'domain_of': ['Publication']} }) + + +class AnnotatorResult(ConfiguredBaseModel): + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'http://w3id.org/ontogpt/core'}) + + subject_text: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'subject_text', 'domain_of': ['AnnotatorResult']} }) + object_id: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'object_id', 'domain_of': ['AnnotatorResult']} }) + object_text: Optional[str] = Field(None, json_schema_extra = { "linkml_meta": {'alias': 'object_text', 'domain_of': ['AnnotatorResult']} }) + + +class Container(ConfiguredBaseModel): + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'https://w3id.org/linkml/examples/personinfo', + 'tree_root': True}) + + persons: Optional[List[Person]] = Field(None, description="""A semicolon-delimited list of people named in the text.""", json_schema_extra = { "linkml_meta": {'alias': 'persons', + 'annotations': {'owl': {'tag': 'owl', + 'value': 'ObjectProperty, ObjectSomeValuesFrom'}}, + 'domain_of': ['Container']} }) + + +class Person(NamedEntity): + """ + A person. + """ + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({'from_schema': 'https://w3id.org/linkml/examples/personinfo'}) + + full_name: Optional[str] = Field(None, description="""The full name of the person.""", json_schema_extra = { "linkml_meta": {'alias': 'full_name', 'domain_of': ['Person']} }) + id: str = Field(..., description="""A unique identifier for the person. This is their full name without spaces or special characters.""", json_schema_extra = { "linkml_meta": {'alias': 'id', 'domain_of': ['NamedEntity', 'Publication', 'Person']} }) + label: Optional[str] = Field(None, description="""The label (name) of the named thing""", json_schema_extra = { "linkml_meta": {'alias': 'label', + 'aliases': ['name'], + 'annotations': {'owl': {'tag': 'owl', + 'value': 'AnnotationProperty, AnnotationAssertion'}}, + 'domain_of': ['NamedEntity'], + 'slot_uri': 'rdfs:label'} }) + original_spans: Optional[List[str]] = Field(None, description="""The coordinates of the original text span from which the named entity was extracted, inclusive. For example, \"10:25\" means the span starting from the 10th character and ending with the 25th character. The first character in the text has index 0. Newlines are treated as single characters. Multivalued as there may be multiple spans for a single text.""", json_schema_extra = { "linkml_meta": {'alias': 'original_spans', + 'annotations': {'prompt.skip': {'tag': 'prompt.skip', 'value': 'true'}}, + 'comments': ['This is determined during grounding and normalization', + 'But is based on the full input text'], + 'domain_of': ['NamedEntity']} }) + + @field_validator('original_spans') + def pattern_original_spans(cls, v): + pattern=re.compile(r"^\d+:\d+$") + if isinstance(v,list): + for element in v: + if isinstance(v, str) and not pattern.match(element): + raise ValueError(f"Invalid original_spans format: {element}") + elif isinstance(v,str): + if not pattern.match(v): + raise ValueError(f"Invalid original_spans format: {v}") + return v + + +# Model rebuild +# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model +ExtractionResult.model_rebuild() +NamedEntity.model_rebuild() +CompoundExpression.model_rebuild() +Triple.model_rebuild() +TextWithTriples.model_rebuild() +TextWithEntity.model_rebuild() +RelationshipType.model_rebuild() +Publication.model_rebuild() +AnnotatorResult.model_rebuild() +Container.model_rebuild() +Person.model_rebuild() diff --git a/src/ontogpt/templates/personinfo.yaml b/src/ontogpt/templates/personinfo.yaml new file mode 100644 index 000000000..163a1fe8d --- /dev/null +++ b/src/ontogpt/templates/personinfo.yaml @@ -0,0 +1,42 @@ +id: https://w3id.org/linkml/examples/personinfo +name: personinfo +prefixes: + linkml: https://w3id.org/linkml/ + personinfo: https://w3id.org/linkml/examples/personinfo/ +imports: + - linkml:types + - core +default_range: string + +default_prefix: personinfo + +classes: + + Container: + tree_root: true + attributes: + persons: + description: >- + A semicolon-delimited list of people named in the text. + multivalued: true + inlined_as_list: true + annotations: + owl: ObjectProperty, ObjectSomeValuesFrom + range: Person + + Person: + is_a: NamedEntity + description: >- + A person. + attributes: + full_name: + description: >- + The full name of the person. + range: string + id: + description: >- + A unique identifier for the person. + This is their full name without spaces + or special characters. + identifier: true + range: string From 29993d8930e5e0aa873e0a4d93ac59b61fca28eb Mon Sep 17 00:00:00 2001 From: caufieldjh Date: Fri, 8 Nov 2024 14:55:21 -0500 Subject: [PATCH 6/7] Further Linting --- src/ontogpt/ontex/extractor.py | 37 +++++++++++++++++----------------- 1 file changed, 19 insertions(+), 18 deletions(-) diff --git a/src/ontogpt/ontex/extractor.py b/src/ontogpt/ontex/extractor.py index 6faf1fec9..b6a82baa7 100644 --- a/src/ontogpt/ontex/extractor.py +++ b/src/ontogpt/ontex/extractor.py @@ -1,7 +1,7 @@ """Tools to extract sub-ontologies and reasoner tasks. -This module provides classes and functions to extract sub-ontologies and reasoner tasks from a -given ontology. These tasks can be used to query or evaluate the ontology using a ReasonerEngine +This module provides classes and functions to extract sub-ontologies and reasoner tasks from a +given ontology. These tasks can be used to query or evaluate the ontology using a ReasonerEngine object. Classes: @@ -20,43 +20,44 @@ LLMReasonMethodType: Enum representing different reasoning method types. Task: Represents a task which is a query on an ontology that has a set of defined answers. OntologyCoherencyTask: Represents a task to determine if an ontology is coherent. - EntailedIndirectSuperClassTask: Represents a task to determine the indirect superclasses of a + EntailedIndirectSuperClassTask: Represents a task to determine the indirect superclasses of a class. - EntailedTransitiveSuperClassTask: Represents a task to determine all transitive superclasses of + EntailedTransitiveSuperClassTask: Represents a task to determine all transitive superclasses of a class. - EntailedSubClassOfExpressionTask: Represents a task to determine the subclasses of a class + EntailedSubClassOfExpressionTask: Represents a task to determine the subclasses of a class expression. EntailedDirectSuperClassTask: Represents a task to determine the direct superclasses of a class. MostRecentCommonSubsumerTask: Represents a task to determine the most specific common ancestors. TaxonConstraintTask: Represents a task to determine inapplicable classes by taxon. - ABoxTask: Represents a task to infer assertions over property chains and transitivity in + ABoxTask: Represents a task to infer assertions over property chains and transitivity in aboxes. TaskCollection: Represents a collection of tasks. OntologyExtractor: Extracts Task objects from an ontology. Functions: TaskCollection.load(file_or_object): Loads a TaskCollection from a file or object. - OntologyExtractor.create_task(task_type, parameters, **kwargs): Creates a task of the specified + OntologyExtractor.create_task(task_type, parameters, **kwargs): Creates a task of the specified type. OntologyExtractor.create_random_tasks(num_tasks_per_type, methods, abox): Creates random tasks. OntologyExtractor.extract_ontology(terms, roots, predicates, include_abox): Extracts an ontology module. - OntologyExtractor.extract_indirect_superclasses_task(subclass, siblings, roots, predicates, + OntologyExtractor.extract_indirect_superclasses_task(subclass, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all indirect superclasses of a class. - OntologyExtractor.extract_transitive_superclasses_task(subclass, siblings, roots, predicates, - select_random, **kwargs): Extracts a task for finding all transitive superclasses of a class. - OntologyExtractor.extract_abox_task(subject, siblings, predicate, select_random, **kwargs): + OntologyExtractor.extract_transitive_superclasses_task(subclass, siblings, roots, predicates, + select_random, **kwargs): Extracts a task for finding all + transitive superclasses of a class. + OntologyExtractor.extract_abox_task(subject, siblings, predicate, select_random, **kwargs): Extracts a task for finding all entailed edges. - OntologyExtractor.extract_most_recent_common_subsumers_task(subclass1, subclass2, siblings, - roots, predicates, select_random, **kwargs): Extracts a task for finding all MRCAs of a pair + OntologyExtractor.extract_most_recent_common_subsumers_task(subclass1, subclass2, siblings, + roots, predicates, select_random, **kwargs): Extracts a task for finding all MRCAs of a pair of classes. - OntologyExtractor.extract_subclass_of_expression_task(superclass, predicate, siblings, - predicates, select_random, **kwargs): Extracts a task for finding all subclasses of a class + OntologyExtractor.extract_subclass_of_expression_task(superclass, predicate, siblings, + predicates, select_random, **kwargs): Extracts a task for finding all subclasses of a class expression. - OntologyExtractor.extract_incoherent_ontology_task(incoherents, siblings, disjoints, - spiked_relationships, roots, select_random, **kwargs): Extracts a task for testing ability + OntologyExtractor.extract_incoherent_ontology_task(incoherents, siblings, disjoints, + spiked_relationships, roots, select_random, **kwargs): Extracts a task for testing ability to find incoherencies based on disjointness axioms. - OntologyExtractor.extract_taxon_constraint_task(term, taxon, siblings, never_in, select_random, + OntologyExtractor.extract_taxon_constraint_task(term, taxon, siblings, never_in, select_random, **kwargs): Extracts a task for evaluating taxon constraints. OntologyExtractor._axiom(rel, tbox): Creates an axiom from a relationship. OntologyExtractor._name(curie): Returns the name of a CURIE. From eb4aa76b62a433fe450c8c523b629d123bcfa300 Mon Sep 17 00:00:00 2001 From: caufieldjh Date: Fri, 8 Nov 2024 14:57:41 -0500 Subject: [PATCH 7/7] Yes it is Linting again --- src/ontogpt/ontex/extractor.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/ontogpt/ontex/extractor.py b/src/ontogpt/ontex/extractor.py index b6a82baa7..b73ca4bbf 100644 --- a/src/ontogpt/ontex/extractor.py +++ b/src/ontogpt/ontex/extractor.py @@ -39,7 +39,7 @@ OntologyExtractor.create_task(task_type, parameters, **kwargs): Creates a task of the specified type. OntologyExtractor.create_random_tasks(num_tasks_per_type, methods, abox): Creates random tasks. - OntologyExtractor.extract_ontology(terms, roots, predicates, include_abox): Extracts an ontology + OntologyExtractor.extract_ontology(terms, roots, predicates, include_abox): Extracts an ontology module. OntologyExtractor.extract_indirect_superclasses_task(subclass, siblings, roots, predicates, select_random, **kwargs): Extracts a task for finding all indirect superclasses of a class.