Triple
T10709103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vienne River |
E252485
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Creuse River |
E665311
|
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: Creuse River | Statement: [Vienne River, hasTributary, Creuse River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Creuse River Context triple: [Vienne River, hasTributary, Creuse River]
-
A.
Creuse River
chosen
The Creuse River is a major river in central France that flows through the historical regions of Berry and Limousin, known for its scenic valleys and picturesque landscapes.
-
B.
Charentonne River
The Charentonne River is a watercourse in northern France that flows through the town of Bernay and contributes to the region’s rural and historical landscape.
-
C.
Creuse
Creuse is a rural department in central France known for its sparsely populated landscapes, traditional agriculture, and part of the historic Limousin region.
-
D.
Sée River
The Sée River is a coastal river in northwestern France that flows through Normandy before emptying into the Bay of Mont-Saint-Michel.
-
E.
Aveyron River
The Aveyron River is a waterway in southern France known for flowing through scenic gorges and historic towns before joining the Tarn River.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fe5063bc8190ba12fd68a59c9a03 |
completed | April 9, 2026, 1:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49c59538081909102a6954f564e46 |
completed | May 1, 2026, 12:28 p.m. |
Created at: April 8, 2026, 9:13 p.m.