Triple
T15670496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay of Saint-Brieuc area |
E377296
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Trégueux |
E1225558
|
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: Trégueux | Statement: [Bay of Saint-Brieuc area, hasPart, Trégueux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trégueux Context triple: [Bay of Saint-Brieuc area, hasPart, Trégueux]
-
A.
Trégueux
chosen
Trégueux is a commune in the Côtes-d'Armor department of Brittany in northwestern France, situated near the city of Saint-Brieuc.
-
B.
Charigot
Charigot is the surname of Aline Charigot, a French woman best known as the model, companion, and later wife of the painter Pierre-Auguste Renoir.
-
C.
Guillestre
Guillestre is a small commune in southeastern France’s Hautes-Alpes department, known as a gateway to the Queyras Regional Natural Park and the surrounding Alpine valleys.
-
D.
Tournus
Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
-
E.
Calvé
Calvé is a well-known food brand, particularly recognized for its peanut butter and sauces, that forms part of Unilever’s global brand portfolio.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f1254508190a77a16b7bfd299ad |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a502c82881908d5b6f7c23e8a403 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 4:16 a.m.