Triple
T16201019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Châteaubriant |
E393197
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Chère |
E1105969
|
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: Chère | Statement: [Châteaubriant, hasRiver, Chère]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chère Context triple: [Châteaubriant, hasRiver, Chère]
-
A.
Chère
chosen
Chère is a river in western France that flows through the Brittany region before joining the Vilaine.
-
B.
Pécharmant
Pécharmant is a French wine appellation in southwest France known for its robust, age-worthy red wines made primarily from Bordeaux grape varieties.
-
C.
Charmes
Charmes is a 1922 poetry collection by French symbolist writer Paul Valéry, noted for its intricate, musical verse and philosophical depth.
-
D.
Clémentine
Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
-
E.
Valentinoise
Valentinoise is the French demonym referring to a female inhabitant of the city of Valence in the Drôme department.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2270aa7f08190ab37aa9ff46816fc |
completed | April 17, 2026, 12:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff130bcc8190a965d90e123d2dd9 |
completed | May 10, 2026, 3:44 a.m. |
Created at: April 10, 2026, 5:03 a.m.