Triple
T14573862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nivelles |
E341986
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object | Benoît Lutgen |
E837884
|
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: Benoît Lutgen | Statement: [Nivelles, hasMayor, Benoît Lutgen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benoît Lutgen Context triple: [Nivelles, hasMayor, Benoît Lutgen]
-
A.
Benoît Lutgen
chosen
Benoît Lutgen is a Belgian politician who has led the francophone centrist party cdH (Centre démocrate humaniste) and held various regional and national political roles.
-
B.
Laurent Brosse
Laurent Brosse is a French local politician who serves as the mayor of the suburban Parisian town of Conflans-Sainte-Honorine.
-
C.
Benoît Delhomme
Benoît Delhomme is a French cinematographer known for his visually distinctive work on international films such as The Scent of Green Papaya, The Theory of Everything, and Lawless.
-
D.
Olivier Basselin
Olivier Basselin was a 15th-century French poet and songwriter from Normandy, known for his drinking songs and influence on the tradition of French popular poetry.
-
E.
Laurent Chalumeau
Laurent Chalumeau is a French writer and screenwriter known for his work in film and literature.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f49d58819094fcd2a702e146cb |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feadfaddc88190bb1196ace0bfd4ff |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 1:24 a.m.