Triple
T29491540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minsara Kanavu |
E748092
|
entity |
| Predicate | hasChoreographyAward |
P187382
|
FINISHED |
| Object | National Film Award for Best Choreography |
—
|
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: National Film Award for Best Choreography | Statement: [Minsara Kanavu, hasChoreographyAward, National Film Award for Best Choreography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChoreographyAward Context triple: [Minsara Kanavu, hasChoreographyAward, National Film Award for Best Choreography]
-
A.
hasJuryAward
Indicates that an entity has received a decision or compensation determined by a jury.
-
B.
hasTonyAward
Indicates that an entity has received or been awarded a Tony Award.
-
C.
hasAwardedForFilmIndustry
Indicates that an entity has given or conferred an award to another entity specifically for achievements in the film industry.
-
D.
hasGivenAcclaimedPerformance
Indicates that an entity has delivered a performance that has received significant praise or critical acclaim.
-
E.
awardedInTheatre
Indicates that an award or honor was given to someone or something specifically for work or achievement in the field of theatre.
- 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_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb563a28d88190b28345c465c545f8 |
completed | May 6, 2026, 2:54 p.m. |
Created at: April 28, 2026, 4:14 p.m.