Triple
T5462230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manthan |
E122618
|
entity |
| Predicate | leadCharacterProfession |
P21567
|
FINISHED |
| Object | veterinary doctor |
—
|
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: veterinary doctor | Statement: [Manthan, leadCharacterProfession, veterinary doctor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterProfession Context triple: [Manthan, leadCharacterProfession, veterinary doctor]
-
A.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
B.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
-
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.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
E.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
- 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_69bd4643f16081908d7f29e08096115a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a370a88190b5d17b8a5387138d |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.