Triple
T5744698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thibault |
E126701
|
entity |
| Predicate | variantOf |
P4680
|
FINISHED |
| Object | Thibaut |
E126701
|
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: Thibaut | Statement: [Thibault, variantOf, Thibaut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thibaut Context triple: [Thibault, variantOf, Thibaut]
-
A.
Thierry
Thierry is a French given name most famously borne by legendary footballer Thierry Henry.
-
B.
Gilles Thibaut
Gilles Thibaut was a French songwriter and lyricist best known for co-writing the classic song "Comme d'habitude," which later became internationally famous as "My Way."
-
C.
Thibault
chosen
Thibault is a surname most notably associated with Mike Thibault, a prominent American basketball coach in the WNBA.
-
D.
Thierry Noir
Thierry Noir is a French artist renowned for being one of the first to paint large, colorful murals on the Berlin Wall, helping transform it into a symbol of artistic and political expression.
-
E.
Benoît
Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c025883b608190b21523da2afde218 |
completed | March 22, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e27ba848190b0c289a804b865cd |
completed | March 22, 2026, 11:41 p.m. |
Created at: March 22, 2026, 3:48 p.m.