Triple
T5918210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lara's Theme |
E131633
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Maurice Jarre |
E133300
|
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: Maurice Jarre | Statement: [Lara's Theme, composer, Maurice Jarre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maurice Jarre Context triple: [Lara's Theme, composer, Maurice Jarre]
-
A.
Maurice Jarre
chosen
Maurice Jarre was a French composer renowned for his sweeping, Oscar-winning film scores, particularly for epic movies such as "Lawrence of Arabia," "Doctor Zhivago," and "A Passage to India."
-
B.
Richard Addinsell
Richard Addinsell was a British composer best known for his film scores and the popular orchestral piece "Warsaw Concerto."
-
C.
Miklós Rózsa
Miklós Rózsa was a Hungarian-American composer renowned for his influential and Oscar-winning film scores during Hollywood’s Golden Age, including classics like Ben-Hur and Double Indemnity.
-
D.
Ernest Gold
Ernest Gold was an Austrian-born American composer best known for his acclaimed film scores, including the Oscar-winning music for "Exodus."
-
E.
Franz Waxman
Franz Waxman was a German-American composer renowned for his influential and Oscar-winning film scores during Hollywood's Golden Age.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c037feb9d8819089bf68e3a4a53534 |
completed | March 22, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c033d59481909495192af85307b7 |
completed | March 23, 2026, 4:23 a.m. |
Created at: March 22, 2026, 3:59 p.m.