Triple
T37109429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salt (2010 film) |
E918943
|
entity |
| Predicate | hasAlternateCuts |
P57506
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Salt (2010 film), hasAlternateCuts, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateCuts Context triple: [Salt (2010 film), hasAlternateCuts, yes]
-
A.
hasAlternateCut
chosen
Indicates that an entity has an alternative edited version or cut, distinct from its primary or original form.
-
B.
hasAlternateTake
Indicates that one entity is an alternative version or different take of another, typically representing a variant recording, shot, or rendition of the same underlying content.
-
C.
hasAlternativeSurface
Indicates that one entity serves as a different or substitute surface option for another entity.
-
D.
hasAlternativeProduction
Indicates that an entity has another possible method, process, or source by which it can be produced or generated.
-
E.
hasAlternativeCrossing
Indicates that there exists another available crossing option that can be used instead of the primary one.
- 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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
Created at: May 3, 2026, 4:14 p.m.