Triple
T22433151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English Vinglish |
E554546
|
entity |
| Predicate | marksReturnToCinemaAfterYears |
P148168
|
FINISHED |
| Object | 15 |
—
|
LITERAL FINISHED |
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: 15 | Statement: [English Vinglish, marksReturnToCinemaAfterYears, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marksReturnToCinemaAfterYears Context triple: [English Vinglish, marksReturnToCinemaAfterYears, 15]
-
A.
hasAfterMovie
Indicates that one movie or media work occurs or is intended to be watched immediately after another as a follow-up or subsequent viewing.
-
B.
endedOnTheater
Indicates that a theatrical run or showing of something (such as a film or play) has concluded at a theater.
-
C.
movedToTheater
Indicates that an entity changed location by going to or entering a theater.
-
D.
servedInTheatres
Indicates that a film or performance was publicly exhibited in movie theaters or similar cinema venues.
-
E.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a3320448190ae3931062599116e |
completed | April 29, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:47 p.m.