Triple
T29417794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dev |
E746070
|
entity |
| Predicate | notableRelativeIndustry |
P367
|
FINISHED |
| Object | Tamil cinema |
E39755
|
NE 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: Tamil cinema | Statement: [Dev, notableRelativeIndustry, Tamil cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableRelativeIndustry Context triple: [Dev, notableRelativeIndustry, Tamil cinema]
-
A.
notableIndustry
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
B.
notable relative occupation
Indicates that a person has a relative whose occupation is notable or significant in some recognized way.
-
C.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
D.
notableRelative
chosen
Indicates that an entity has a relative who is notable or well-known, specifying that familial relationship.
-
E.
notableIndustryInArea
Indicates that a particular industry is especially prominent, significant, or well-known within a given geographic area.
- F. None of above.
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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a035ac41d088190b7e76b93c1410090 |
completed | May 12, 2026, 4:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a27641c05a4819091086247aa913cd8 |
completed | June 9, 2026, 12:53 a.m. |
| PD | Predicate disambiguation | batch_6a035a4f290c8190a0101295a38ae8b8 |
completed | May 12, 2026, 4:50 p.m. |
Created at: April 28, 2026, 3:02 p.m.