Triple
T29492287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mersal |
E748112
|
entity |
| Predicate | featuresActorInTripleRole |
P200146
|
FINISHED |
| Object | Vijay |
—
|
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: Vijay | Statement: [Mersal, featuresActorInTripleRole, Vijay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresActorInTripleRole Context triple: [Mersal, featuresActorInTripleRole, Vijay]
-
A.
featuresActorInMultipleRoles
Indicates that a work includes an actor who portrays more than one distinct role within that same work.
-
B.
playedInEnsembleWith
Indicates that one entity has performed together with another as members of the same musical ensemble or group.
-
C.
oftenPlayedBySingleActor
Indicates that the same single actor frequently portrays or performs this role, character, or part across multiple instances or productions.
-
D.
hasTwinActors
Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within a given context.
-
E.
hasPortrayedPersonRole
Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
- F. None of above. chosen
Provenance (4 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_69f0bd448c6881908aa6b475cefd5ddc |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69ff779e3f0c8190a861f1e4000fd9d9 |
completed | May 9, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69ff77202638819086e4b9f9c0bc7b31 |
completed | May 9, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69ff779d3d788190af5a2dbc4d7ca3c8 |
completed | May 9, 2026, 6:06 p.m. |
Created at: April 28, 2026, 4:15 p.m.