Triple
T18449477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jura (canton) |
E450740
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Basse-Allaine |
—
|
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: Basse-Allaine | Statement: [Jura (canton), hasMunicipality, Basse-Allaine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Basse-Allaine Context triple: [Jura (canton), hasMunicipality, Basse-Allaine]
-
A.
Basse-Allaine
chosen
Basse-Allaine is a municipality in the predominantly rural, French-speaking canton of Jura in northwestern Switzerland.
-
B.
Basse-Goulaine
Basse-Goulaine is a commune in the Loire-Atlantique department in western France, situated in the suburban area southeast of Nantes.
-
C.
Cottévrard
Cottévrard is a small commune in the Seine-Maritime department of the Normandy region in northern France.
-
D.
Cheneux
Cheneux is a small village in the municipality of Stoumont in the province of Liège, Belgium, known for its rural setting and World War II history.
-
E.
La Bresse
La Bresse is a French mountain town in northeastern France known for its ski resort and outdoor activities in the Vosges.
- 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.