Triple
T15710996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Take It All |
E380835
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Marion Cotillard |
E135915
|
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: Marion Cotillard | Statement: [Take It All, performer, Marion Cotillard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marion Cotillard Context triple: [Take It All, performer, Marion Cotillard]
-
A.
Marion Cotillard
chosen
Marion Cotillard is an acclaimed French actress known for her versatile performances in both French and Hollywood films, including her Oscar-winning role in "La Vie en Rose."
-
B.
Bérénice Bejo
Bérénice Bejo is a French-Argentine actress best known internationally for her acclaimed performance in the silent film "The Artist."
-
C.
Juliette Binoche
Juliette Binoche is an acclaimed French actress known for her nuanced performances in international cinema and her Academy Award-winning role in "The English Patient."
-
D.
Jean-Marie Binoche
Jean-Marie Binoche is a French actor and director best known as the father of acclaimed actress Juliette Binoche.
-
E.
Cate Blanchett
Cate Blanchett is an acclaimed Australian actress renowned for her versatile performances in both independent films and major Hollywood productions, earning numerous awards including Oscars, Golden Globes, and BAFTAs.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82f22fc88190820ecb171041136d |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:45 a.m.