Triple
T23339796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taking Lives |
E591701
|
entity |
| Predicate | containsAlternateCut |
P57506
|
FINISHED |
| Object | unrated director's cut |
—
|
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: unrated director's cut | Statement: [Taking Lives, containsAlternateCut, unrated director's cut]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsAlternateCut Context triple: [Taking Lives, containsAlternateCut, unrated director's cut]
-
A.
hasAlternateCut
chosen
Indicates that an entity has an alternative edited version or cut, distinct from its primary or original form.
-
B.
hasCut
Indicates that one entity has made or possesses a cut in, on, or through another entity.
-
C.
isCutInto
Indicates that one entity is divided or separated into pieces or segments that become the other entity.
-
D.
hasTypicalCut
Indicates that one entity is characterized by or associated with a standard or typical type of cut of another entity.
-
E.
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.
- 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_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f198317f4c8190a557cacb86568d6c |
completed | April 29, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69effcfd8d288190937a887fe6023c11 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:18 p.m.