Triple
T12167263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac de Guéry |
E289865
|
entity |
| Predicate | watercourse |
P415
|
FINISHED |
| Object | Sioule |
E271845
|
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: Sioule | Statement: [Lac de Guéry, watercourse, Sioule]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sioule Context triple: [Lac de Guéry, watercourse, Sioule]
-
A.
Sioule
chosen
The Sioule is a river in central France that flows through the Auvergne region before joining the Allier River.
-
B.
Simiche
Simiche is a central character in Menander’s ancient Greek comedy "Dyskolos," around whom much of the play’s domestic and social conflict revolves.
-
C.
Marlais
Marlais is the distinctive middle name of Welsh poet and writer Dylan Thomas, reflecting his Welsh heritage.
-
D.
Matapouri
Matapouri is a small coastal settlement in New Zealand known for its scenic beach, sheltered bay, and nearby natural attractions such as Mermaid Pools.
-
E.
Houlle
Houlle is a small commune in northern France’s Pas-de-Calais department, known for its rural character and traditional French countryside setting.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d85c088190a74fb7590877659b |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6a45568819090662cd3547c9253 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.