Triple
T1524915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ennio Morricone |
E32312
|
entity |
| Predicate | numberOfFilmScores |
P30144
|
FINISHED |
| Object | over 400 |
—
|
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: over 400 | Statement: [Ennio Morricone, numberOfFilmScores, over 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFilmScores Context triple: [Ennio Morricone, numberOfFilmScores, over 400]
-
A.
academyAwardForBestMusicScoringOfADramaticOrComedyPicture
Indicates that an entity received the Academy Award for Best Music Scoring of a Dramatic or Comedy Picture for a particular film.
-
B.
typicalNumberOfSelectedFilms
Indicates the usual or average number of films that are chosen or selected in a given context or process.
-
C.
filmSoundtrackFor
Indicates that a particular soundtrack is created for, associated with, or used as the official musical accompaniment to a specific film.
-
D.
numberOfFilmsAppearedIn
Indicates the total count of distinct films in which a given entity has appeared.
-
E.
soundtrackType
Indicates the specific category or format of a soundtrack associated with a work, such as score, compilation, or original soundtrack.
- F. None of above. chosen
Provenance (4 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93d4756888190bf3872154de11539 |
completed | March 5, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69a907ac7ea081908dd95bb5cc3b9847 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a93d462f208190b27ef5cd631bce12 |
completed | March 5, 2026, 8:22 a.m. |
Created at: March 4, 2026, 7:26 p.m.