Triple
T29947326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seema Raja |
E760669
|
entity |
| Predicate | starsInRuralRole |
P42172
|
FINISHED |
| Object | Sivakarthikeyan |
—
|
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: Sivakarthikeyan | Statement: [Seema Raja, starsInRuralRole, Sivakarthikeyan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starsInRuralRole Context triple: [Seema Raja, starsInRuralRole, Sivakarthikeyan]
-
A.
starOccupation
Indicates that an entity is the primary or featured performer in a particular occupation, role, or professional capacity.
-
B.
semiRuralCharacter
Indicates that a place or area has characteristics intermediate between rural and urban, combining elements of both environments.
-
C.
playsInRole
chosen
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
D.
roleInFilmEcosystem
Indicates the specific function or position an entity holds within the broader network of activities, stakeholders, and processes that make up the film ecosystem.
-
E.
entertainmentRole
Indicates that an entity holds a specific function or position within an entertainment context (such as a role in a performance, production, or media 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_69f2246562b881909d57622f4086d43d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6780d1b948190a1a8ca4f34d93cb3 |
completed | May 2, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:24 p.m.