Triple
T6084987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ram Nath Kovind |
E135614
|
entity |
| Predicate | professionStart |
P2214
|
FINISHED |
| Object | advocate at the Supreme Court of India |
—
|
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: advocate at the Supreme Court of India | Statement: [Ram Nath Kovind, professionStart, advocate at the Supreme Court of India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionStart Context triple: [Ram Nath Kovind, professionStart, advocate at the Supreme Court of India]
-
A.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
B.
careerStart
chosen
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
C.
careerType
Indicates the kind or category of professional occupation or career path associated with an entity.
-
D.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
-
E.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057891dc88190997c4e32b2261fb3 |
completed | March 22, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:12 p.m.