Triple
T9846043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnès Varda |
E239344
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Agnès |
E499651
|
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: Agnès | Statement: [Agnès Varda, givenName, Agnès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Agnès Context triple: [Agnès Varda, givenName, Agnès]
-
A.
Agnès
chosen
Agnès is the naive young ward in Molière’s comedy "L’École des femmes," whose sheltered upbringing and awakening to love drive the play’s central conflict.
-
B.
Bénédicte
Bénédicte is the given name of Louise Bénédicte de Bourbon, a French noblewoman of the House of Bourbon.
-
C.
Catherine Brelet
Catherine Brelet is a French film producer best known as the wife and longtime collaborator of acclaimed Swedish actor Max von Sydow.
-
D.
Clara Beranger
Clara Beranger was an American screenwriter of the silent film era, known for her work with Paramount Pictures and her contributions to early Hollywood cinema.
-
E.
Renée
Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb35ff7848190a8a717773d8654b9 |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5e1b67c8190ad7b57ea423511d8 |
completed | April 5, 2026, 3:24 a.m. |
Created at: March 30, 2026, 8:34 p.m.