Triple
T33636803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rang De Basanti |
E861719
|
entity |
| Predicate | hasStoryContributor |
P30146
|
FINISHED |
| Object | Kamal Hassan (story contributor) |
—
|
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: Kamal Hassan (story contributor) | Statement: [Rang De Basanti, hasStoryContributor, Kamal Hassan (story contributor)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStoryContributor Context triple: [Rang De Basanti, hasStoryContributor, Kamal Hassan (story contributor)]
-
A.
hasContributionFrom
chosen
Indicates that something (such as a work, project, or outcome) is created, influenced, or supported in part by a specified contributor.
-
B.
hasAwardInStory
Indicates that an entity is depicted within a narrative or story as having received a particular award.
-
C.
hasAffiliationInStory
Indicates that one entity is affiliated with, associated with, or connected to another entity within the context of a specific story or narrative.
-
D.
hasInfluentialStory
Indicates that one entity possesses or is associated with a story that significantly shapes, impacts, or guides the beliefs, actions, or development of another entity.
-
E.
hasAuthor
Indicates that an entity is written or created by a specific author.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff5803c02c81908b63067119f5e684 |
completed | May 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69ff576d8b308190b49a1e072a0ae661 |
completed | May 9, 2026, 3:49 p.m. |
Created at: May 1, 2026, 1:42 a.m.