Triple
T13166282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Thonon-les-Bains |
E312857
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Abondance |
E912632
|
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: Abondance | Statement: [arrondissement of Thonon-les-Bains, contains, Abondance]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abondance Context triple: [arrondissement of Thonon-les-Bains, contains, Abondance]
-
A.
Abondance
Abondance is a Cubist painting by French artist Henri Le Fauconnier, recognized for its bold geometric forms and vibrant, fragmented depiction of figures and space.
-
B.
Abondance
chosen
Abondance is a traditional alpine village in the French Haute-Savoie region, renowned for its namesake cheese and picturesque mountain setting.
-
C.
Auregnais
Auregnais is an extinct Norman dialect once spoken on the Channel Island of Alderney.
-
D.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
E.
Marlais
Marlais is the distinctive middle name of Welsh poet and writer Dylan Thomas, reflecting his Welsh heritage.
- 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.