Triple
T9076080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wernicke's aphasia |
E217486
|
entity |
| Predicate | typicalLesionLobe |
P87067
|
FINISHED |
| Object | temporal lobe |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: temporal lobe | Statement: [Wernicke's aphasia, typicalLesionLobe, temporal lobe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLesionLobe Context triple: [Wernicke's aphasia, typicalLesionLobe, temporal lobe]
-
A.
typicalOnsetLocation
Indicates the anatomical location where a condition, symptom, or process most commonly begins or first appears.
-
B.
lesionAssociatedWithSymptom
Indicates that a particular lesion is linked to, or occurs together with, a specific symptom.
-
C.
hasLobes
Indicates that an entity possesses distinct rounded or projecting parts (lobes) as characteristic features of its form or structure.
-
D.
pathologyFeature
Indicates that one entity is a pathological characteristic, sign, or abnormal finding associated with another entity in a medical or biological context.
-
E.
treatsAnatomicalSite
Indicates that an action, intervention, or agent is directed toward and intended to treat a specific anatomical site.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc95c53274819099b3b3047bfe8cc8 |
completed | April 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3c78388190a7436acc0e44ff55 |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:12 p.m.