Triple
T33245690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rajiv Menon |
E851092
|
entity |
| Predicate | hasWorkedAsCinematographerOn |
P90619
|
FINISHED |
| Object | Bombay |
—
|
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: Bombay | Statement: [Rajiv Menon, hasWorkedAsCinematographerOn, Bombay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkedAsCinematographerOn Context triple: [Rajiv Menon, hasWorkedAsCinematographerOn, Bombay]
-
A.
cinematographerOfWork
chosen
Indicates that a person served as the cinematographer (director of photography) for a specific creative work.
-
B.
cinematographyNotedFor
Indicates that the subject’s cinematography is especially recognized or distinguished for the object (such as a particular work, style, or notable quality).
-
C.
hasWorkedOnFilmBy
Indicates that one entity has worked on a film that was created, directed, or otherwise authored by another entity.
-
D.
workedBehindTheCameraAs
Indicates that a person contributed to a production in an off-screen or non-acting role, such as directing, producing, or other behind-the-scenes work.
-
E.
workedOnFilmReleasedBy
Indicates that one entity contributed work to a film that was distributed or released by another entity.
- 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_69f34962386c81909ddc3bf9e18ddeb8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: May 1, 2026, 1:31 a.m.