Triple
T2747010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sébastien Le Prestre de Vauban |
E60893
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sébastien |
E278395
|
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: Sébastien | Statement: [Sébastien Le Prestre de Vauban, givenName, Sébastien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sébastien Context triple: [Sébastien Le Prestre de Vauban, givenName, Sébastien]
-
A.
Sébastien
chosen
Sébastien is the French form of the given name Sebastian, commonly used in French-speaking countries.
-
B.
Clément
Clément is a French given name, equivalent to Clement in English, commonly used for males.
-
C.
Virage Chatillon
Virage Chatillon is a French youth football club known for being one of the early teams in Thierry Henry’s development.
-
D.
Lucas Secon
Lucas Secon is a Danish-American record producer, songwriter, and artist known for his work across pop and hip-hop with acts such as The Pussycat Dolls, Kylie Minogue, and Christina Aguilera.
-
E.
Stéphane
Stéphane is a French masculine given name, equivalent to Stephen in English, commonly used in Francophone 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_69ab4b79846081909096725374d65ce9 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb4ed6bc8190876c1d188b97692b |
completed | March 7, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbbd0f3a08190bf33a937ae9749c7 |
completed | March 10, 2026, 6:36 a.m. |
Created at: March 6, 2026, 9:56 p.m.