Triple
T10193401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gueugnon |
E238095
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object | Arroux |
E671645
|
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: Arroux | Statement: [Gueugnon, river, Arroux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arroux Context triple: [Gueugnon, river, Arroux]
-
A.
Arroux
chosen
Arroux is a river in central France that flows through the Burgundy region before joining the Loire.
-
B.
Orléat
Orléat is a small commune in central France’s Puy-de-Dôme department, known for its rural character within the Auvergne region.
-
C.
Debourg
Debourg is a tram terminus and transport hub in Lyon, France, serving as one end of the city’s T1 tram line.
-
D.
Peseux
Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
-
E.
Douaumont
Douaumont is a small commune in northeastern France best known for its World War I battlefield sites near Verdun, including major memorials and military cemeteries.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc675008190b8248325f5a208bf |
completed | April 2, 2026, 4:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317d3c1bc8190811b809aaf93a754 |
completed | April 6, 2026, 2:17 a.m. |
Created at: March 30, 2026, 9:13 p.m.