Triple
T23679227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telugu people |
E584971
|
entity |
| Predicate | cinemaCenter |
P151607
|
FINISHED |
| Object | Hyderabad |
—
|
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: Hyderabad | Statement: [Telugu people, cinemaCenter, Hyderabad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cinemaCenter Context triple: [Telugu people, cinemaCenter, Hyderabad]
-
A.
cinemaOf
Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
-
B.
cinemaStatus
Indicates the current operational or functional state of a cinema, such as whether it is open, closed, or otherwise restricted.
-
C.
theatreCity
chosen
Indicates that a theatre is located in, or primarily associated with, a particular city.
-
D.
filmSettingTheater
Indicates that a film’s setting or key scenes take place in a theater (such as a cinema or playhouse).
-
E.
cinemaCategory
Indicates the classification or genre category assigned to a cinema or film.
- 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f5a7b48190b93d27416003e173 |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:51 p.m.