Triple
T32641472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vital |
E834488
|
entity |
| Predicate | hasMedicalStudentProtagonist |
P197569
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Vital, hasMedicalStudentProtagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalStudentProtagonist Context triple: [Vital, hasMedicalStudentProtagonist, true]
-
A.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
B.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
C.
hasMedicalDramaElements
Indicates that something contains themes, plotlines, or stylistic features characteristic of medical drama stories or shows.
-
D.
hasMedicalAttendant
Indicates that one entity serves as a medical attendant (e.g., providing medical care or supervision) for another entity.
-
E.
hasProtagonistCondition
Indicates that the main character in a narrative has a particular condition, state, or affliction.
- 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_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fe9b0276d48190b554fa22b043e6d8 |
completed | May 9, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69fe999692b081909921e1148d66f0ef |
completed | May 9, 2026, 2:19 a.m. |
| PDg | Predicate description generation | batch_69fe9b013ec481908f89beddb9c4cd4e |
completed | May 9, 2026, 2:25 a.m. |
Created at: May 1, 2026, 1:07 a.m.