Triple
T29301222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velu Naicker |
E742961
|
entity |
| Predicate | filmCinematographer |
P90619
|
FINISHED |
| Object | P. C. Sreeram |
—
|
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: P. C. Sreeram | Statement: [Velu Naicker, filmCinematographer, P. C. Sreeram]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmCinematographer Context triple: [Velu Naicker, filmCinematographer, P. C. Sreeram]
-
A.
cinematographerOfWork
chosen
Indicates that a person served as the cinematographer (director of photography) for a specific creative work.
-
B.
cinematographyBy
Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
-
C.
notableCinematographer
Indicates that the subject is a cinematographer who is particularly distinguished or well-known for their work.
-
D.
cinematographyAwardedTo
Indicates that a cinematography-related award has been given to a particular recipient (such as a person or team) for their work.
-
E.
cinematographyAwardNominee
Indicates that an entity was nominated to receive an award specifically recognizing excellence in cinematography.
- 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_69f09123ed9881909f351f7541933f5e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f665a2ab44819080b1c5f711c229e4 |
completed | May 2, 2026, 8:59 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 1:10 p.m.