diff --git a/efo/fetch_efo_ontology_from_pubmed.py b/efo/fetch_efo_ontology_from_pubmed.py
index 1b038ea..4b2e7c7 100644
--- a/efo/fetch_efo_ontology_from_pubmed.py
+++ b/efo/fetch_efo_ontology_from_pubmed.py
@@ -48,8 +48,6 @@
 tasks = query_labels(graph, "Task")
 concepts = query_labels(graph, "ExecutiveFunction")
 
-print(tasks)
-
 print(f"Tasks: {len(tasks)}, Concepts: {len(concepts)}")
 
 time_estimate = len(tasks) * len(concepts)
@@ -65,6 +63,29 @@
 #tasks = ["Reversal Learning"]
 #concepts = ["Behavioral Control"]
 
+def build_queries(task, concept):
+    return {
+    'task_concept_ef_hits':             f'("{task}"[TIAB]) AND ("{concept}"[TIAB]) AND ("executive function")',
+    'task_suffixtask_concept_ef_hits':  f'("{task} task"[TIAB]) AND ("{concept}"[TIAB]) AND ("executive function")',
+    'task_suffixtest_concept_ef_hits':  f'("{task} test"[TIAB]) AND ("{concept}"[TIAB]) AND ("executive function")',
+    'task_suffixgame_concept_ef_hits':  f'("{task} game"[TIAB]) AND ("{concept}"[TIAB]) AND ("executive function")',
+    'task_concept_hits':                f'("{task}"[TIAB]) AND ("{concept}"[TIAB])',
+    'task_suffixtask_concept_hits':     f'("{task} task"[TIAB]) AND ("{concept}"[TIAB])',
+    'task_suffixtest_concept_hits':     f'("{task} test"[TIAB]) AND ("{concept}"[TIAB])',
+    'task_suffixgame_concept_hits':     f'("{task} game"[TIAB]) AND ("{concept}"[TIAB])',
+    'concept_hits':                     f'("{concept}"[TIAB])',
+    'concept_ef_hits':                  f'("{concept}"[TIAB]) AND ("executive function")',
+    'task_hits':                        f'("{task}"[TIAB])',
+    'task_suffixtask_hits':             f'("{task} task"[TIAB])',
+    'task_suffixtest_hits':             f'("{task} test"[TIAB])',
+    'task_suffixgame_hits':             f'("{task} game"[TIAB])',
+    'task_ef_hits':                     f'("{task}"[TIAB]) AND ("executive function")',
+    'task_suffixtask_ef_hits':          f'("{task} task"[TIAB]) AND ("executive function")',
+    'task_suffixgame_ef_hits':          f'("{task} game"[TIAB]) AND ("executive function")',
+    'task_suffixtest_ef_hits':          f'("{task} test"[TIAB]) AND ("executive function")'
+    }
+
+
 def query_pubmed_for_task(task, concept):
     suffixes = ['',' task',' game',' test']
     task_queries = map(lambda s: task+s, suffixes)
@@ -81,7 +102,7 @@
 
 # main loop
 
-with open("data/efo_taskconcept_pubmed_hits.csv", "a+") as csv:
+with open("data/efo_taskconcept_pubmed_hits.csv", "a",buffering=1) as csv:
     csv.write('task,concept,hits,suffixed_hits,concept_hits,timestamp_ms\n')
     for task, concept in [(task, concept) for task in tasks for concept in concepts]:
         millis = int(round(time.time() * 1000))
@@ -95,3 +116,29 @@
         
         print(csv_line)
         csv.write(csv_line)
+
+
+#%%
+# Partial lookup: only queries pubmed if a combination of task-concept is not already fetched.
+import pandas as pd
+
+csv_file = "data/efo_taskconcept_pubmed_hits.csv"
+
+fetcher = PubMedFetcher()
+data = pd.read_csv(csv_file)
+
+with open("data/efo_taskconcept_pubmed_hits.csv", "a",buffering=1) as csv:
+    for task, concept in [(task, concept) for task in tasks for concept in concepts]:
+        task_df = data[(data.task == task) & (data.concept == concept)]
+        if task_df.empty:
+            millis = int(round(time.time() * 1000))
+
+            hits, suffixed_hits = query_pubmed_for_task(task, concept)
+
+            concept_query = f"({concept}[TIAB])"
+            concept_hits = fetcher.pmids_for_query(query=f'{concept_query}', retmax=1000000, pmc_only=False)
+            
+            csv_line = f'{task},{concept},{len(hits)},{len(suffixed_hits)},{len(concept_hits)},{millis}\n'
+            
+            print(csv_line)
+            csv.write(csv_line)
\ No newline at end of file