Triple
T2236801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seine River Basin |
E49299
|
entity |
| Predicate | containsRiver |
P165
|
FINISHED |
| Object | Yonne |
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 | Statement: [Seine River Basin, containsRiver, Yonne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yonne Context triple: [Seine River Basin, containsRiver, Yonne]
-
A.
Yonne
chosen
Yonne is a major river in north-central France that flows through the Burgundy region before joining the Seine.
-
B.
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.
-
C.
Loiret
Loiret is a department in north-central France, named after the Loiret River and known for its historic towns and proximity to the Loire Valley.
-
D.
Loir
The Loir is a river in central France that flows through the regions of Pays de la Loire and Centre-Val de Loire before joining the Sarthe.
-
E.
Aisne
Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc09573848190bf91eddcc2fa0061 |
completed | March 7, 2026, 6:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e38ff2881909490b7b20deb149b |
completed | March 13, 2026, 3:02 a.m. |
Created at: March 4, 2026, 7:47 p.m.