Triple
T18449475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jura (canton) |
E450740
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Saignelégier |
—
|
NE NERFINISHED |
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: Saignelégier | Statement: [Jura (canton), hasMunicipality, Saignelégier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saignelégier Context triple: [Jura (canton), hasMunicipality, Saignelégier]
-
A.
Saignelégier
chosen
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
-
B.
Lussy
Lussy is a small municipality in the Glâne District of the canton of Fribourg in western Switzerland.
-
C.
Chassieu
Chassieu is a commune in the Metropolis of Lyon in eastern France, known for its residential areas and proximity to the Lyon urban center.
-
D.
Gueugnon
Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
-
E.
Villeroux
Villeroux is a small village in the municipality of Vaux-sur-Sûre in the Walloon region of Belgium.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5264748dc8190984501af3e4b2036 |
completed | April 19, 2026, 7 p.m. |
Created at: April 10, 2026, 11:30 a.m.