Triple
T15646584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Migennes |
E376192
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object | Yonne River |
E44545
|
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: Yonne River | Statement: [Migennes, river, Yonne River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yonne River Context triple: [Migennes, river, Yonne River]
-
A.
Yonne
chosen
Yonne is a major river in north-central France that flows through the Burgundy region before joining the Seine.
-
B.
Essonne River
The Essonne River is a tributary of the Seine in northern France, flowing through the Île-de-France region and giving its name to the Essonne department.
-
C.
Aube River
The Aube River is a major waterway in northeastern France that flows through the Champagne region before joining the Seine.
-
D.
Nièvre
Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
-
E.
Allier River
The Allier River is a major river in central France, known for its largely unspoiled natural course and as a tributary of the Loire.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fffee4f84c81908b2c7e216ef159e0 |
completed | May 10, 2026, 3:43 a.m. |
Created at: April 10, 2026, 4:15 a.m.