Triple
T13166288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Thonon-les-Bains |
E312857
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Lugrin |
E643814
|
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: Lugrin | Statement: [arrondissement of Thonon-les-Bains, contains, Lugrin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lugrin Context triple: [arrondissement of Thonon-les-Bains, contains, Lugrin]
-
A.
Lugrin
chosen
Lugrin is a commune in eastern France on the southern shore of Lake Geneva, known historically as one of the sites where the Évian Accords negotiations took place.
-
B.
Cazeneuve
Cazeneuve is a French surname most notably borne by Bernard Cazeneuve, a prominent French politician and former Prime Minister of France.
-
C.
Noailles
Noailles is a renowned art district in Croix-des-Bouquets, Haiti, famous for its vibrant community of metal sculptors and artisans.
-
D.
Courcier
Courcier was a French publishing house known for issuing important mathematical and scientific works in the early 19th century.
-
E.
Boucicaut
Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c2c317881908cc715c97d915f77 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eaf6c9ec8190bc0097d62e57e52a |
completed | May 3, 2026, 6:28 a.m. |
Created at: April 9, 2026, 9:13 p.m.