Triple
T4337442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Wore a Yellow Ribbon |
E97497
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Richard Hageman |
E449445
|
NE 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: Richard Hageman | Statement: [She Wore a Yellow Ribbon, musicBy, Richard Hageman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richard Hageman Context triple: [She Wore a Yellow Ribbon, musicBy, Richard Hageman]
-
A.
Richard Hageman
chosen
Richard Hageman was a Dutch-born American composer and conductor best known for his film scores, including his Academy Award-winning work on classic Hollywood Westerns.
-
B.
Daniel P. Hanley
Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
-
C.
Allen M. Davey
Allen M. Davey was an American cinematographer known for his work on early Technicolor films in Hollywood.
-
D.
George Hildebrand
George Hildebrand was an American Major League Baseball umpire active in the early 20th century.
-
E.
Thomas F. Hofmann
Thomas F. Hofmann is a German food chemist and academic leader who serves as president of the Technical University of Munich.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3516c621881909f094d040d4805e9 |
completed | March 12, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd36a7c9c81908f325bc8a53db0c8 |
completed | March 20, 2026, 11:08 p.m. |
Created at: March 12, 2026, 11:14 p.m.