Triple
T29745996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vijay Sethupathi |
E752751
|
entity |
| Predicate | alsoWorksIn |
P106564
|
FINISHED |
| Object | Telugu 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: Telugu cinema | Statement: [Vijay Sethupathi, alsoWorksIn, Telugu cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoWorksIn Context triple: [Vijay Sethupathi, alsoWorksIn, Telugu cinema]
-
A.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
B.
hasWorksIn
Indicates that one entity is employed by or performs their professional activities within the organization, location, or context represented by another entity.
-
C.
laterWorksAt
Indicates that an entity begins working at a place or organization at a time later than another referenced time or employment situation.
-
D.
alsoIn
chosen
Indicates that an entity participates in or belongs to an additional context, group, or location alongside another already specified one.
-
E.
involvedInWork
Indicates that an entity participates in, contributes to, or is otherwise engaged in a particular work, project, or activity.
- 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_69f0d62b064081908c1ae61cd68fb139 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67367c41c8190a750374567b8e782 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:51 p.m.