Triple
T22076091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C. Ramchandra |
E545524
|
entity |
| Predicate | workedFor |
P1910
|
FINISHED |
| Object | Bombay 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: Bombay film industry | Statement: [C. Ramchandra, workedFor, Bombay film industry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bombay film industry Context triple: [C. Ramchandra, workedFor, Bombay film industry]
-
A.
Nollywood
Nollywood is Nigeria’s prolific film industry, renowned as one of the largest movie producers in the world and a major cultural force across Africa.
-
B.
Bollywood cinema
chosen
Bollywood cinema is the mainstream Hindi-language film industry based in Mumbai, India, known for its song-and-dance musicals, melodrama, and massive cultural influence across South Asia and the global Indian diaspora.
-
C.
Kollywood
Kollywood is the Tamil-language film industry based in Chennai, India, known for its prolific output of commercial and artistic cinema.
-
D.
Lollywood
Lollywood is the Pakistani film industry based in Lahore, historically known for producing Punjabi- and Urdu-language movies.
-
E.
Pollywood
Pollywood is the regional film industry based in the Indian state of Punjab, producing Punjabi-language movies and entertainment content.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b2bf60819082d38e671f160b0f |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:28 p.m.