Triple
T5694513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anupam Kher as Dr. Cliff Patel |
E125504
|
entity |
| Predicate | professionInFiction |
P34569
|
FINISHED |
| Object | therapist |
—
|
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: therapist | Statement: [Anupam Kher as Dr. Cliff Patel, professionInFiction, therapist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionInFiction Context triple: [Anupam Kher as Dr. Cliff Patel, professionInFiction, therapist]
-
A.
fictionalOccupation
chosen
Indicates that one entity is the imaginary or narrative-based job, role, or profession attributed to another entity within a fictional context.
-
B.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
C.
creativeRole
Indicates that an entity holds a specific creative function or responsibility in relation to another entity, such as a work or project.
-
D.
genreOfWorkCharacterIsIn
Indicates the specific genre of the creative work in which a given character appears.
-
E.
producerInFiction
Indicates that an entity serves as a producer (e.g., of a show, film, or other work) within a fictional context or narrative.
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c0e0408190ab6c3cd3f907e80f |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.