Triple
T33201465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Srinivas |
E849909
|
entity |
| Predicate | sangForFilmIndustry |
P176180
|
FINISHED |
| Object | Tamil film industry |
—
|
NE NERFINISHED |
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: Tamil film industry | Statement: [Srinivas, sangForFilmIndustry, Tamil film industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sangForFilmIndustry Context triple: [Srinivas, sangForFilmIndustry, Tamil film industry]
-
A.
originatesInFilmIndustry
Indicates that something has its source, development, or primary origin within the film industry.
-
B.
popularFilmIndustry
Indicates that an entity has a widely recognized and well-liked film industry that attracts significant audience interest and attention.
-
C.
occupationInFilm
Indicates that an entity has a specific occupation or role within the context of a particular film.
-
D.
hasAwardedForFilmIndustry
Indicates that an entity has given or conferred an award to another entity specifically for achievements in the film industry.
-
E.
sungInFilmBy
Indicates that a particular song was vocally performed in a film by a specific person or group.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
| PDg | Predicate description generation | batch_69f6dd3b335481909e24d4eb5b0269f9 |
completed | May 3, 2026, 5:29 a.m. |
Created at: May 1, 2026, 1:29 a.m.