Triple
T29415835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A. V. Meiyappan |
E746023
|
entity |
| Predicate | roleInCinema |
P55759
|
FINISHED |
| Object | key figure in development of Tamil cinema |
—
|
LITERAL 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: key figure in development of Tamil cinema | Statement: [A. V. Meiyappan, roleInCinema, key figure in development of Tamil cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInCinema Context triple: [A. V. Meiyappan, roleInCinema, key figure in development of Tamil cinema]
-
A.
roleInCinerama
Indicates that an entity has a role or participation in a Cinerama film or production.
-
B.
bookingRole
Indicates the role or capacity an entity has in relation to a booking (e.g., who made, manages, or is responsible for the booking).
-
C.
theaterRole
Indicates that an entity holds or performs a specific role or character in a theatrical production in relation to another entity (such as a play or performance).
-
D.
roleInLoewsCorporation
Indicates that one entity holds or has held a specific role, position, or office within Loews Corporation in relation to the other entity.
-
E.
roleInFilmEcosystem
chosen
Indicates the specific function or position an entity holds within the broader network of activities, stakeholders, and processes that make up the film ecosystem.
- 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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fefa064ab48190925759950d0d94d9 |
completed | May 9, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69fef96ae5d08190b027435753c44821 |
completed | May 9, 2026, 9:07 a.m. |
Created at: April 28, 2026, 3:01 p.m.