Triple
T892574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Buffett |
E19272
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Dances with Wolves (score contributions)
Dances with Wolves (score contributions) refers to Peter Buffett’s work composing and contributing music to the acclaimed film score of the 1990 Western epic "Dances with Wolves."
|
E105951
|
NE FINISHED |
How this triple was built (4 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: Dances with Wolves (score contributions) | Statement: [Peter Buffett, notableWork, Dances with Wolves (score contributions)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dances with Wolves (score contributions) Context triple: [Peter Buffett, notableWork, Dances with Wolves (score contributions)]
-
A.
How the West Was Won (film score)
How the West Was Won is a sweeping orchestral film score for the 1962 epic Western, renowned for its grand, Americana-infused themes and expansive musical storytelling.
-
B.
The Thin Red Line (1998 film) score
The Thin Red Line (1998 film) score is a contemplative, minimalist war film soundtrack by Hans Zimmer, noted for its haunting themes, use of recurring motifs, and emotional depth.
-
C.
The Last Samurai (2003 film) score
The Last Samurai (2003 film) score is a sweeping, emotionally charged orchestral soundtrack by Hans Zimmer that blends Western symphonic elements with traditional Japanese instrumentation to underscore the film’s epic and introspective themes.
-
D.
The Clan of the Cave Bear (film score)
The Clan of the Cave Bear (film score) is a dramatic orchestral soundtrack composed by Alan Silvestri for the 1986 prehistoric adventure film adaptation of Jean M. Auel’s novel.
-
E.
Forrest Gump (film score)
Forrest Gump (film score) is the orchestral soundtrack composed by Alan Silvestri, renowned for its emotive themes that underscore the film’s sweeping, nostalgic narrative.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dances with Wolves (score contributions) Triple: [Peter Buffett, notableWork, Dances with Wolves (score contributions)]
Generated description
Dances with Wolves (score contributions) refers to Peter Buffett’s work composing and contributing music to the acclaimed film score of the 1990 Western epic "Dances with Wolves."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dances with Wolves (score contributions) Target entity description: Dances with Wolves (score contributions) refers to Peter Buffett’s work composing and contributing music to the acclaimed film score of the 1990 Western epic "Dances with Wolves."
-
A.
How the West Was Won (film score)
How the West Was Won is a sweeping orchestral film score for the 1962 epic Western, renowned for its grand, Americana-infused themes and expansive musical storytelling.
-
B.
The Thin Red Line (1998 film) score
The Thin Red Line (1998 film) score is a contemplative, minimalist war film soundtrack by Hans Zimmer, noted for its haunting themes, use of recurring motifs, and emotional depth.
-
C.
The Last Samurai (2003 film) score
The Last Samurai (2003 film) score is a sweeping, emotionally charged orchestral soundtrack by Hans Zimmer that blends Western symphonic elements with traditional Japanese instrumentation to underscore the film’s epic and introspective themes.
-
D.
The Clan of the Cave Bear (film score)
The Clan of the Cave Bear (film score) is a dramatic orchestral soundtrack composed by Alan Silvestri for the 1986 prehistoric adventure film adaptation of Jean M. Auel’s novel.
-
E.
Forrest Gump (film score)
Forrest Gump (film score) is the orchestral soundtrack composed by Alan Silvestri, renowned for its emotive themes that underscore the film’s sweeping, nostalgic narrative.
- F. None of above. chosen
Provenance (5 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad0304b081908d4c92bb2beadb81 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c025464081908032939637248635 |
completed | March 4, 2026, 5:16 a.m. |
| NEDg | Description generation | batch_69a7c227893c8190a4ce35637365014f |
completed | March 4, 2026, 5:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7c2f1d0508190ad47eeb8099fd9f9 |
completed | March 4, 2026, 5:28 a.m. |
Created at: March 1, 2026, 7:39 p.m.