Triple
T35735740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UGC |
E1032880
|
entity |
| Predicate | hasCinemaChain |
P188138
|
FINISHED |
| Object | UGC cinemas |
—
|
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: UGC cinemas | Statement: [UGC, hasCinemaChain, UGC cinemas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCinemaChain Context triple: [UGC, hasCinemaChain, UGC cinemas]
-
A.
hasMovieTheater
Indicates that one entity possesses, contains, or includes a movie theater as part of its facilities or attributes.
-
B.
hasNumberOfCinemas
Indicates the quantity of cinemas associated with a given entity.
-
C.
belongsToCinema
Indicates that something is part of, associated with, or under the ownership/management of a particular cinema.
-
D.
hasCinemaOperator
Indicates that a cinema is operated, managed, or run by a specific organization or individual.
-
E.
hasNumberOfTheatres
Indicates the quantity of theatres associated with or present in a given entity.
- 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_69f76e10e59081908d81ad9ce22f40b6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69fba28684208190921694f23e350c3b |
completed | May 6, 2026, 8:20 p.m. |
Created at: May 3, 2026, 4:05 p.m.