Triple
T8890681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emergency Room |
E211653
|
entity |
| Predicate | treatsConditionType |
P85563
|
FINISHED |
| Object | Acute illness |
—
|
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: Acute illness | Statement: [Emergency Room, treatsConditionType, Acute illness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsConditionType Context triple: [Emergency Room, treatsConditionType, Acute illness]
-
A.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
B.
supportsTreatmentType
Indicates that one entity is capable of providing, handling, or is compatible with a specified type of treatment.
-
C.
hasCommonTreatment
Indicates that two or more entities share at least one treatment method or therapeutic approach in common.
-
D.
usesTreatment
Indicates that one entity applies or employs a particular treatment or therapeutic method on or for another entity.
-
E.
hasTypicalConditions
Indicates that something is associated with conditions or circumstances that are commonly or normally present for it.
- 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_69ca83907954819096d52a245b635841 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc619188508190aacda410f0b4c98d |
completed | April 1, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5d6e54808190af4156edd4c8ffbc |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 6:53 p.m.