Triple
T17025982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Millionaire’s Express |
E413063
|
entity |
| Predicate | hasGenreInfluenceFrom |
P20936
|
FINISHED |
| Object | Western genre |
—
|
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: Western genre | Statement: [Millionaire’s Express, hasGenreInfluenceFrom, Western genre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenreInfluenceFrom Context triple: [Millionaire’s Express, hasGenreInfluenceFrom, Western genre]
-
A.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
B.
influencedByGenre
chosen
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
C.
influenceOnGenre
Indicates how strongly one entity has shaped, affected, or contributed to the development or characteristics of a particular genre.
-
D.
influencesMusicOf
Indicates that one entity has an effect on, shapes, or contributes to the musical style, content, or development of another entity.
-
E.
influencedArtist
Indicates that one artist has had a significant impact on the style, work, or development of another artist.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d46a5081908bc5681621dd8534 |
completed | April 18, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.