Triple
T19098492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthieu Chedid |
E467467
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Matthieu |
—
|
NE NERFINISHED |
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: Matthieu | Statement: [Matthieu Chedid, givenName, Matthieu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthieu Context triple: [Matthieu Chedid, givenName, Matthieu]
-
A.
Matthieu
chosen
Matthieu is a French masculine given name, equivalent to Matthew in English.
-
B.
Baptiste
Baptiste is a British crime drama television series centered on the character of detective Julien Baptiste, a spin-off from the series "The Missing."
-
C.
Clément
Clément is a French given name, equivalent to Clement in English, commonly used for males.
-
D.
Benoît
Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
-
E.
Thibault
Thibault is a surname most notably associated with Mike Thibault, a prominent American basketball coach in the WNBA.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36b279c819091a8d51f044bc644 |
completed | April 20, 2026, 8:27 a.m. |
Created at: April 10, 2026, 12:04 p.m.