Triple
T10191157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seine-et-Oise |
E238036
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Oise |
E326194
|
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: Oise | Statement: [Seine-et-Oise, namedAfter, Oise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oise Context triple: [Seine-et-Oise, namedAfter, Oise]
-
A.
Oise
Oise is a major river in northern France that flows through regions such as Picardy and Île-de-France before joining the Seine near Paris.
-
B.
Vosgien
Vosgien is a regional dialect of the Lorrain language spoken in the Vosges area of northeastern France.
-
C.
Oise River
chosen
The Oise River is a major waterway in northern France and southern Belgium that flows into the Seine and serves as an important route for inland navigation and commerce.
-
D.
Vallée de la Marne
Vallée de la Marne is a key subregion of France’s Champagne wine area, known for its vineyards along the Marne River and its significant production of Pinot Meunier–based sparkling wines.
-
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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7eb1148190a2d175163685e233 |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f6e73a2881908563e9e6a02df944 |
completed | April 9, 2026, 12:46 a.m. |
Created at: March 30, 2026, 9:13 p.m.