diff --git a/my_experiments/ibd_literature/test.txt b/my_experiments/ibd_literature/test.txt
new file mode 100644
index 000000000..1f2ad8bdf
--- /dev/null
+++ b/my_experiments/ibd_literature/test.txt
@@ -0,0 +1,5 @@
+Subject	Predicate	Object
+inflammatory bowel disease	pro-inflammatory	cytokine production
+ulcerative colitis	to	arachidonic acid metabolic process
+ulcerative colitis	relieving	inflammatory response
+ulcerative colitis	and	inflammatory response
diff --git a/output_parser_yaml.py b/output_parser_yaml.py
new file mode 100644
index 000000000..b0dc6913d
--- /dev/null
+++ b/output_parser_yaml.py
@@ -0,0 +1,40 @@
+import yaml
+from yaml import CLoader as Loader
+from oaklib import get_adapter
+
+NULL_VALS = ['', 'Not mentioned', 'none mentioned', 'Not mentioned in the text', 
+             'Not mentioned in the provided text.', 'No exposures mentioned in the text.', 
+             'None', 'N/A', 'No exposures mentioned in the text.', 'None mentioned in the text', 
+             'Not mentioned in the text.', 'None relevant', 'None mentioned in the text.', 
+             'No gene to molecular activity relationships mentioned in the text.',
+             'No genes mentioned', 'No genes mentioned in the text.', 'NA', '-',
+             'None mentioned']
+output_file = "experiments/ibd_literature/output_2000_1122.yaml"
+    
+def filter_dictionary(input_dict, filter_keys):
+    filtered_dict = {key: value for key, value in input_dict.items() if key in filter_keys}
+    return filtered_dict
+
+with open(output_file, 'r') as file:
+    filtered_data = []
+    for doc in yaml.safe_load_all(file):
+        try:
+            for dict in doc["extracted_object"]["disease_cellular_process_relationships"]:
+                filtered_data.append(filter_dictionary(dict, ["subject", "predicate", "object"]))
+        except:
+            continue
+
+for entry in filtered_data:
+    if (len(entry) == 3 and
+        entry["subject"] not in NULL_VALS and
+        entry["predicate"] not in NULL_VALS and
+        entry["object"] not in NULL_VALS):
+        if (entry["subject"].startswith("MONDO:") and
+            entry["object"].startswith("GO:")):
+            entry["subject"] = get_adapter("sqlite:obo:MONDO").label(entry["subject"])
+            # if entry["predicate"].startswith("RO:"):
+            #     entry["predicate"] = get_adapter("sqlite:obo:RO").label(entry["predicate"])
+            entry["object"] = get_adapter("sqlite:obo:GO").label(entry["object"])
+            if entry["predicate"].startswith("RO:"):
+                entry["predicate"] = get_adapter("sqlite:obo:RO").label(entry["predicate"])
+            print(entry)
\ No newline at end of file
diff --git a/src/ontogpt/cli.py b/src/ontogpt/cli.py
index b9e8cfe91..3867df7f6 100644
--- a/src/ontogpt/cli.py
+++ b/src/ontogpt/cli.py
@@ -46,6 +46,7 @@
 from ontogpt.io.csv_wrapper import output_parser, write_obj_as_csv
 from ontogpt.io.html_exporter import HTMLExporter
 from ontogpt.io.markdown_exporter import MarkdownExporter
+from ontogpt.io.template_loader import get_template_details
 from ontogpt.utils.gene_set_utils import (
     GeneSet,
     _is_human,
@@ -63,6 +64,10 @@
 from ontogpt.io.yaml_wrapper import dump_minimal_yaml
 from ontogpt.templates.core import ExtractionResult
 
+from ontogpt.converters.output_filtered_triples import output_filtered_triples
+# from ontogpt.converters.output_filtered_triples import edit_yaml
+from ontogpt.converters.output_filtered_triples import read_template
+
 
 @dataclass
 class Settings:
@@ -312,12 +317,21 @@ def extract(
     elif inputfile and not Path(inputfile).exists():
         raise FileNotFoundError(f"Cannot find input file {inputfile}")
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template=template, model=model_name, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.client.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.client.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         ke = GPT4AllEngine(template=template, model=model_name, **kwargs)
@@ -357,14 +371,22 @@ def generate_extract(model, entity, template, output, output_format, show_prompt
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         model_name = selectmodel["alternative_names"][0]
@@ -413,14 +435,22 @@ def iteratively_generate_extract(
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         model_name = selectmodel["alternative_names"][0]
@@ -461,14 +491,22 @@ def pubmed_extract(model, pmid, template, output, output_format, get_pmc, show_p
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         model_name = selectmodel["alternative_names"][0]
@@ -518,14 +556,22 @@ def pubmed_annotate(
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         model_name = selectmodel["alternative_names"][0]
@@ -559,14 +605,22 @@ def wikipedia_extract(model, article, template, output, output_format, show_prom
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template=template, model=model, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         model_name = selectmodel["alternative_names"][0]
@@ -600,14 +654,18 @@ def wikipedia_search(model, topic, keyword, template, output, output_format, sho
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template=template, model=model, **kwargs)
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
 
-    elif model_source == "GPT4All":
-        model_name = selectmodel["alternative_names"][0]
-        ke = GPT4AllEngine(template=template, model=model_name, **kwargs)
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
 
     logging.info(f"Creating for {template} => {topic}")
     client = WikipediaClient()
@@ -652,14 +710,18 @@ def search_and_extract(
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template, **kwargs)
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
 
-    elif model_source == "GPT4All":
-        model_name = selectmodel["alternative_names"][0]
-        ke = GPT4AllEngine(template=template, model=model_name, **kwargs)
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
 
     term = " ".join(term_tokens)
     logging.info(f"Creating for {template}; search={term} kw={keyword}")
@@ -698,14 +760,22 @@ def web_extract(model, template, url, output, output_format, show_prompt, **kwar
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template=template, model=model, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         model_name = selectmodel["alternative_names"][0]
@@ -748,14 +818,22 @@ def recipe_extract(
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template, **kwargs)
-        if settings.cache_db:
-            ke.client.cache_db_path = settings.cache_db
-        if settings.skip_annotators:
-            ke.skip_annotators = settings.skip_annotators
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
+    if settings.cache_db:
+        ke.client.cache_db_path = settings.cache_db
+    if settings.skip_annotators:
+        ke.skip_annotators = settings.skip_annotators
 
     elif model_source == "GPT4All":
         model_name = selectmodel["alternative_names"][0]
@@ -800,14 +878,18 @@ def convert(model, template, input, output, output_format, **kwargs):
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template, **kwargs)
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
 
-    elif model_source == "GPT4All":
-        model_name = selectmodel["alternative_names"][0]
-        ke = GPT4AllEngine(template=template, model=model_name, **kwargs)
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
 
     cls = ke.template_pyclass
     with open(input, "r") as f:
@@ -1464,7 +1546,7 @@ def eval_enrichment(genes, input_file, number_to_drop, annotations_path, model,
     default=False,
     show_default=True,
     help="If set, chunk input text, then prepare a separate prompt for each chunk."
-            " Otherwise the full input text is passed.",
+    " Otherwise the full input text is passed.",
 )
 @click.argument("evaluator")
 def eval(evaluator, num_tests, output, chunking, model, **kwargs):
@@ -1477,10 +1559,9 @@ def eval(evaluator, num_tests, output, chunking, model, **kwargs):
     else:
         modelname = DEFAULT_MODEL
 
-    evaluator = create_evaluator(name=evaluator,
-                                 num_tests=num_tests,
-                                 chunking=chunking,
-                                 model=modelname)
+    evaluator = create_evaluator(
+        name=evaluator, num_tests=num_tests, chunking=chunking, model=modelname
+    )
     eos = evaluator.eval()
     output.write(dump_minimal_yaml(eos, minimize=False))
 
@@ -1504,13 +1585,18 @@ def fill(model, template, object: str, examples, output, output_format, show_pro
     if not model:
         model = DEFAULT_MODEL
     selectmodel = get_model_by_name(model)
-    model_source = selectmodel["provider"]
 
-    if model_source == "OpenAI":
-        ke = SPIRESEngine(template=template, **kwargs)
+    if template:
+        template_details = get_template_details(template=template)
     else:
-        model_name = selectmodel["alternative_names"][0]
-        ke = GPT4AllEngine(template=template, model=model_name, **kwargs)
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(
+        template_details=template_details,
+        model=selectmodel["alternative_names"][0],
+        model_source=selectmodel["provider"].lower(),
+        **kwargs,
+    )
 
     object = yaml.safe_load(object)
     logging.info(f"Object to fill =  {object}")
@@ -1562,8 +1648,13 @@ def complete(model, input, output, output_format, show_prompt, **kwargs):
 @click.option("--input", "-i", type=click.File("r"), default=sys.stdin, help="Input file")
 def parse(template, input):
     """Parse OpenAI results."""
-    logging.info(f"Creating for {template}")
-    ke = SPIRESEngine(template)
+
+    if template:
+        template_details = get_template_details(template=template)
+    else:
+        raise ValueError("No template specified. Use -t/--template option.")
+
+    ke = SPIRESEngine(template_details=template_details)
     text = input.read()
     logging.debug(f"Input text: {text}")
     # ke.annotator = BioPortalImplementation()
@@ -1697,6 +1788,103 @@ def clinical_notes(
     output.write(results)
 
 
+@main.command()
+@click.option("-i", "--input", help="Input file.")
+@click.option("-o", "--output", help="Output file.")
+@click.option("--subject-prefix", default = "MONDO", help="Prefix for subject.")
+@click.option("--object-prefix", default = "GO", help="Prefix for object.")
+@click.option("--pred-prefix", default = "RO", help="Prefix for predicate.")
+def get_triples(input, output, subject_prefix, object_prefix, pred_prefix):
+    """Filter YAML format extraction output to s, p, o triples.
+
+    Example:
+
+        ontogpt get-triples -i extracted.yaml -o extracted.tsv --subject-prefix MONDO --object-prefix GO --pred-prefix RO
+
+    """
+    triples = output_filtered_triples(input, subject_prefix, object_prefix, pred_prefix)
+    
+    with open(output, "w") as file:
+        file.write("Subject\tPredicate\tObject\n")
+        for triple in triples:
+            file.write("\t".join(triple.values()))
+            file.write("\n")
+
+@main.command()
+@template_option
+@prompt_template_option
+@model_option
+@recurse_option
+@output_option_wb
+@output_format_options
+@show_prompt_option
+@click.option(
+    "--limit",
+    default=20,
+    help="Total number of citation records to return.",
+)
+@click.option(
+    "--get-pmc/--no-get-pmc",
+    default=False,
+    help="Attempt to parse PubMed Central full text(s) instead of abstract(s) alone.",
+)
+# @click.option("--subject-prefix", default = "MONDO", help="Prefix for subject.")
+# @click.option("--object-prefix", default = "GO", help="Prefix for object.")
+# @click.option("--pred-prefix", default = "RO", help="Prefix for predicate.")
+@click.option("--subject-prefix", default = None, help = "Prefix for subject.")
+@click.option("--object-prefix", default = None, help = "Prefix for object.")
+@click.option("--pred-prefix", default = None, help = "Prefix for predicate.")
+@click.argument("search")
+def pubmed_annotate_template_alter(
+    model, search, template, prompt_template, output, output_format, limit, get_pmc, show_prompt, subject_prefix, object_prefix, pred_prefix, **kwargs
+):
+    """Retrieve a collection of PubMed IDs for a search term; annotate them using a template.
+
+    Example:
+    ontogpt pubmed-annotate-template-alter -t ibd_literature 
+        --prompt-template src/ontogpt/templates/ibd_literature.yaml "inflammatory bowel disease"
+        --limit 2000 -o output.yaml -O yaml --subject-prefix CHEBI --object-prefix GO --pred-prefix RO
+    
+    """
+
+    contents = read_template(prompt_template, subject_prefix, object_prefix, pred_prefix)
+
+    pubmed_annotate(model, search, contents, output, output_format, limit, get_pmc, show_prompt)
+
+    """logging.info(f"Creating for {template}")
+
+    edit_yaml(template, subject_prefix, object_prefix, pred_prefix)
+
+    if not model:
+        model = DEFAULT_MODEL
+    selectmodel = get_model_by_name(model)
+    model_source = selectmodel["provider"]
+
+    if model_source == "OpenAI":
+        ke = SPIRESEngine(template, **kwargs)
+        if settings.cache_db:
+            ke.client.cache_db_path = settings.cache_db
+        if settings.skip_annotators:
+            ke.skip_annotators = settings.skip_annotators
+
+    elif model_source == "GPT4All":
+        model_name = selectmodel["alternative_names"][0]
+        ke = GPT4AllEngine(template=template, model=model_name, **kwargs)
+
+    pubmed_annotate_limit = limit
+    pmc = PubmedClient()
+    pmids = pmc.get_pmids(search)
+    if get_pmc:
+        logging.info("Will try to retrieve PubMed Central texts.")
+        textlist = pmc.text(pmids[: pubmed_annotate_limit + 1], pubmedcental=True)
+    else:
+        textlist = pmc.text(pmids[: pubmed_annotate_limit + 1])
+    for text in textlist:
+        logging.debug(f"Input text: {text}")
+        results = ke.extract_from_text(text=text, show_prompt=show_prompt)
+        write_extraction(results, output, output_format, ke)"""
+
+
 @main.command()
 def list_templates():
     """List the templates."""
diff --git a/src/ontogpt/converters/output_filtered_triples.py b/src/ontogpt/converters/output_filtered_triples.py
new file mode 100644
index 000000000..62e786da5
--- /dev/null
+++ b/src/ontogpt/converters/output_filtered_triples.py
@@ -0,0 +1,86 @@
+import yaml
+from yaml import CLoader as Loader
+from oaklib import get_adapter
+
+NULL_VALS = [
+    "",
+    "Not mentioned",
+    "none mentioned",
+    "Not mentioned in the text",
+    "Not mentioned in the provided text.",
+    "No exposures mentioned in the text.",
+    "None",
+    "N/A",
+    "No exposures mentioned in the text.",
+    "None mentioned in the text",
+    "Not mentioned in the text.",
+    "None relevant",
+    "None mentioned in the text.",
+    "No gene to molecular activity relationships mentioned in the text.",
+    "No genes mentioned",
+    "No genes mentioned in the text.",
+    "NA",
+    "-",
+    "None mentioned",
+]
+
+def edit_yaml(template, subject_prefix, object_prefix, pred_prefix):
+    def object_based_add(prefix, isAnnotator):
+        if isAnnotator:
+            if isinstance(prefix, str):
+                return "sqlite:obo:" + prefix.lower()
+            elif isinstance(prefix, list):
+                prefix_full = ["sqlite:obo:" + pf.lower() for pf in prefix]
+                return ", ".join(prefix_full)
+        else:
+            if isinstance(prefix, str):
+                return [prefix]
+            elif isinstance(prefix, list):
+                return prefix
+
+    with open(template, "r") as file:
+        contents = yaml.safe_load(file)
+        contents["classes"]["Disease"]["id_prefixes"] = object_based_add(subject_prefix, False)
+        contents["classes"]["Disease"]["annotations"]["annotators"] = object_based_add(subject_prefix, True)
+        contents["classes"]["CellularProcess"]["id_prefixes"] = object_based_add(object_prefix, False)
+        contents["classes"]["CellularProcess"]["annotations"]["annotators"] = object_based_add(object_prefix, True)
+        contents["classes"]["DiseaseToCellularProcessPredicate"]["id_prefixes"] = object_based_add(pred_prefix, False)
+        contents["classes"]["DiseaseToCellularProcessPredicate"]["annotations"]["annotators"] = object_based_add(pred_prefix, True)
+    
+    with open(template, "w") as file:
+        yaml.dump(contents, file, sort_keys = False)
+
+def output_filtered_triples(input_file, subject_prefix, object_prefix, pred_prefix):
+    filtered_data = []
+
+    def filter_dictionary(input_dict, filter_keys):
+        filtered_dict = {key: value for key, value in input_dict.items() if key in filter_keys}
+        return filtered_dict
+
+    # TODO:
+    # 0. Don't need to call get_adapter every time - just once is fine for each annotator
+    # 1. This does not handle situations where the subject or object or predicate is a list of values
+    # 2. This does not handle situations where any of the above are None (as in, not specified)
+    # 3. This does not handle situations where the input triples may be missing s, p, or o
+    # 4. This does not allow us to not label s, p, or o
+    # 5. This makes the assumption that the adapter is the same as the prefix
+    with open(input_file, "r") as file:
+        for doc in yaml.safe_load_all(file):
+            try:
+                for dict in doc["extracted_object"]["disease_cellular_process_relationships"]:
+                    entry = filter_dictionary(dict, ["subject", "predicate", "object"])
+                    if (len(entry) == 3
+                        and entry["subject"] not in NULL_VALS
+                        and entry["predicate"] not in NULL_VALS
+                        and entry["object"] not in NULL_VALS
+                        ):
+                        if entry["subject"].startswith(f"{subject_prefix}:") and entry["object"].startswith(f"{object_prefix}:"):
+                            entry["subject"] = get_adapter(f"sqlite:obo:{subject_prefix}").label(entry["subject"])
+                            entry["object"] = get_adapter(f"sqlite:obo:{object_prefix}").label(entry["object"])
+                            if entry["predicate"].startswith(f"{pred_prefix}:"):
+                                entry["predicate"] = get_adapter(f"sqlite:obo:{pred_prefix}").label(entry["predicate"])
+                            filtered_data.append(entry)
+            except:
+                continue
+
+    return filtered_data
diff --git a/src/ontogpt/engines/knowledge_engine.py b/src/ontogpt/engines/knowledge_engine.py
index cb6da8e74..47dd41036 100644
--- a/src/ontogpt/engines/knowledge_engine.py
+++ b/src/ontogpt/engines/knowledge_engine.py
@@ -81,9 +81,9 @@ class KnowledgeEngine(ABC):
     knowledge sources plus LLMs
     """
 
-    template: TEMPLATE_NAME = ""
-    """LinkML Template to use for this engine.
-    Must be of the form <module_name>.<ClassName>"""
+    template_details: tuple
+    """Tuple containing loaded template details, including:
+    (LinkML class, module, python class, SchemaView object)"""
 
     template_class: ClassDefinition = None
     """LinkML Class for the template.
@@ -152,8 +152,13 @@ class KnowledgeEngine(ABC):
     encoding = None
 
     def __post_init__(self):
-        if self.template:
-            self.template_class = self._get_template_class(self.template)
+        if self.template_details:
+            (
+                self.template_class,
+                self.template_module,
+                self.template_pyclass,
+                self.schemaview,
+            ) = self.template_details
         if self.template_class:
             logging.info(f"Using template {self.template_class.name}")
         if not self.model:
diff --git a/src/ontogpt/templates/ibd_literature_test.yaml b/src/ontogpt/templates/ibd_literature_test.yaml
new file mode 100644
index 000000000..5020680ef
--- /dev/null
+++ b/src/ontogpt/templates/ibd_literature_test.yaml
@@ -0,0 +1,76 @@
+id: http://w3id.org/ontogpt/ibd_literature
+name: ibd-literature-template
+title: IBD Literature Template
+description: A template for extracting information from IBD literature
+license: https://creativecommons.org/publicdomain/zero/1.0/
+prefixes:
+  CHEBI: http://purl.obolibrary.org/obo/CHEBI_
+  ECTO: http://purl.obolibrary.org/obo/ECTO_
+  ExO: http://purl.obolibrary.org/obo/ExO_
+  HGNC: http://identifiers.org/hgnc/
+  NCIT: http://purl.obolibrary.org/obo/NCIT_
+  MONDO: http://purl.obolibrary.org/obo/MONDO_
+  GO: http://purl.obolibrary.org/obo/GO_
+  core: http://w3id.org/ontogpt/core/
+  ibdlit: http://w3id.org/ontogpt/ibd_literature/
+  linkml: https://w3id.org/linkml/
+default_prefix: ibdlit
+default_range: string
+imports:
+- linkml:types
+- core
+classes:
+  IBDAnnotations:
+    tree_root: true
+    attributes:
+      diseases:
+        description: semicolon-separated list of diseases
+        multivalued: true
+        range: Disease
+      cellular_process:
+        description: semicolon-separated list of cellular processes
+        multivalued: true
+        range: CellularProcess
+      disease_cellular_process_relationships:
+        description: semicolon-separated list of disease to cellular process relationships
+        multivalued: true
+        range: DiseaseCellularProcessRelationship
+  Disease:
+    is_a: NamedEntity
+    id_prefixes:
+    - MONDO
+    annotations:
+      annotators: sqlite:obo:mondo
+      prompt: the name of the disease
+  CellularProcess:
+    is_a: NamedEntity
+    id_prefixes:
+    - GO
+    annotations:
+      annotators: sqlite:obo:go
+      prompt: the name of the cellular process
+  DiseaseToCellularProcessPredicate:
+    is_a: NamedEntity
+    id_prefixes:
+    - RO
+    annotations:
+      annotators: sqlite:obo:ro
+      prompt: the name of the type of relationship between a disease and a cellular
+        process.
+  DiseaseCellularProcessRelationship:
+    is_a: CompoundExpression
+    attributes:
+      subject:
+        range: Disease
+        description: The name of the disease.
+      predicate:
+        range: DiseaseToCellularProcessPredicate
+        description: The name of the type of relationship between a disease and a
+          cellular process.
+      object:
+        range: CellularProcess
+        description: The name of the cellular process.
+      subject_qualifier:
+        range: NamedEntity
+      object_qualifier:
+        range: NamedEntity