Triple
T3542903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léon Bottou |
E74927
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Léon |
E70702
|
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: Léon | Statement: [Léon Bottou, givenName, Léon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Léon Context triple: [Léon Bottou, givenName, Léon]
-
A.
Léon
chosen
Léon is a French surname borne by various notable individuals across fields such as politics, arts, and academia.
-
B.
Léon: The Professional
Léon: The Professional is a 1994 crime thriller film by Luc Besson about a hitman who forms an unusual bond with a young girl after her family is murdered.
-
C.
Le Beau Serge
Le Beau Serge is a 1958 French film by Claude Chabrol, widely regarded as one of the first works of the French New Wave movement.
-
D.
Polisse
Polisse is a 2011 French drama film directed by Maïwenn that follows a Paris police child protection unit, noted for its gritty realism and ensemble cast.
-
E.
L’Argent
L’Argent is an 1891 novel by Émile Zola that explores the corrupting power of finance and speculation within the broader Rougon-Macquart series.
- 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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbf752dd481909226044ffe595338 |
completed | March 8, 2026, 6:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bdd0cb4819086119b54c2708850 |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:20 p.m.