Triple
T2209922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Pierre Cortot |
E50890
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jean-Pierre |
E27779
|
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: Jean-Pierre | Statement: [Jean-Pierre Cortot, givenName, Jean-Pierre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean-Pierre Context triple: [Jean-Pierre Cortot, givenName, Jean-Pierre]
-
A.
Jean-Pierre
chosen
Jean-Pierre is a French given name commonly used as a masculine compound first name.
-
B.
Jean-Claude Olivier
Jean-Claude Olivier is a writer associated with the Juicy brand or publication.
-
C.
Jacques
Jacques is the French form of the given name James, commonly used in French-speaking countries.
-
D.
Peter Biziou
Peter Biziou is a British cinematographer known for his work on films such as "Bugsy Malone" and the Oscar-winning "Mississippi Burning."
-
E.
Julien BriseBois
Julien BriseBois is a Canadian ice hockey executive best known for building and leading the Tampa Bay Lightning into a modern NHL powerhouse and multiple-time Stanley Cup champion.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfce5abc8190b90b92e32045385d |
completed | March 7, 2026, 6:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af176447d881909173c62cc8c394a0 |
completed | March 9, 2026, 6:54 p.m. |
Created at: March 4, 2026, 7:46 p.m.