Triple
T31212959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Grand Duel |
E795797
|
entity |
| Predicate | composerReuse |
P91997
|
FINISHED |
| Object | Luis Bacalov score used by Quentin Tarantino |
—
|
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: Luis Bacalov score used by Quentin Tarantino | Statement: [The Grand Duel, composerReuse, Luis Bacalov score used by Quentin Tarantino]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: composerReuse Context triple: [The Grand Duel, composerReuse, Luis Bacalov score used by Quentin Tarantino]
-
A.
composer
Indicates that one entity is the creator or writer of a musical work associated with another entity.
-
B.
composerOn
Indicates that one entity serves as the composer or creator of a musical or audio work associated with another entity.
-
C.
composerSource
Indicates that one entity is the source or origin of the composer associated with another entity.
-
D.
reusesStructureOf
Indicates that one entity adopts or incorporates the structural design or organization of another entity.
-
E.
reusedIn
chosen
Indicates that something previously used in one context or instance is used again in another context or instance.
- 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_69f224d9d52c8190a61f68ded37fa755 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: April 29, 2026, 9:09 p.m.