Triple
T29300088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madras Talkies |
E742933
|
entity |
| Predicate | frequentEditorCollaborator |
P129005
|
FINISHED |
| Object | Sreekar Prasad |
—
|
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: Sreekar Prasad | Statement: [Madras Talkies, frequentEditorCollaborator, Sreekar Prasad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentEditorCollaborator Context triple: [Madras Talkies, frequentEditorCollaborator, Sreekar Prasad]
-
A.
collaboratorRole
Indicates the specific function, position, or capacity in which one collaborator participates in a shared activity or project with another.
-
B.
co-editedWith
Indicates that two or more entities jointly served as editors of the same work or publication.
-
C.
primaryCollaborator
Indicates that one entity serves as the main or most significant partner working jointly with another entity on a shared activity, project, or goal.
-
D.
frequentlyCollaboratedWith
chosen
Indicates that two entities have worked together on shared activities or projects on a recurring or regular basis.
-
E.
editorOfWork
Indicates that one entity serves as the editor responsible for preparing, revising, or overseeing the content of a particular work.
- 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_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 28, 2026, 1:09 p.m.