Triple
T13403583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dominique Pinon |
E319894
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Diva |
E874912
|
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: Diva | Statement: [Dominique Pinon, notableWork, Diva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diva Context triple: [Dominique Pinon, notableWork, Diva]
-
A.
Diva
"Diva" is a swaggering, club-ready R&B/pop track by Beyoncé that celebrates female confidence and star power.
-
B.
Diva
chosen
Diva is a 1981 French cult thriller film by Jean-Jacques Beineix, celebrated for its stylish visuals, blending of genres, and influence on the cinéma du look movement.
-
C.
Diva Donna
Diva Donna is the onstage persona representing Donna Summer at the height of her fame in the jukebox musical "Summer: The Donna Summer Musical."
-
D.
Diva’s Lament
Diva’s Lament is a comedic show-stopping solo number from the Broadway musical *Spamalot*, in which the Lady of the Lake humorously complains about her lack of stage time and the demands placed on divas.
-
E.
Il Divo
Il Divo is a multinational classical crossover vocal group known for blending operatic technique with popular songs in multiple languages.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae4ae47081909b68a9aaa62fd4c7 |
completed | April 12, 2026, 2:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7307904608190ad647f741c08dc42 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:34 p.m.