Triple
T21117472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evanna Lynch |
E520334
|
entity |
| Predicate | hasMedicalHistory |
P37550
|
FINISHED |
| Object | anorexia nervosa |
—
|
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: anorexia nervosa | Statement: [Evanna Lynch, hasMedicalHistory, anorexia nervosa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalHistory Context triple: [Evanna Lynch, hasMedicalHistory, anorexia nervosa]
-
A.
hasHistoryOf
chosen
Indicates that an entity has a documented prior occurrence or background of a specified condition, event, or state.
-
B.
hasPriorHistory
Indicates that an entity has a previously recorded occurrence, condition, or involvement relevant to the current context.
-
C.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
D.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
E.
hadCondition
Indicates that an entity experienced or was diagnosed with a particular medical or health-related condition.
- F. None of above.
Provenance (3 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e721078ac48190980441b6ada0e2b4 |
completed | April 21, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:55 p.m.