Triple
T14556104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vilaine |
E341545
|
entity |
| Predicate | tributary |
P415
|
FINISHED |
| Object |
Chère
Chère is a river in western France that flows through the Brittany region before joining the Vilaine.
|
E1105969
|
NE FINISHED |
How this triple was built (4 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: [Vilaine, tributary, Chère]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chère Context triple: [Vilaine, tributary, Chère]
-
A.
Pécharmant
Pécharmant is a French wine appellation in southwest France known for its robust, age-worthy red wines made primarily from Bordeaux grape varieties.
-
B.
Charmes
Charmes is a 1922 poetry collection by French symbolist writer Paul Valéry, noted for its intricate, musical verse and philosophical depth.
-
C.
Clémentine
Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
-
D.
Valentinoise
Valentinoise is the French demonym referring to a female inhabitant of the city of Valence in the Drôme department.
-
E.
Mademoiselle Chambon
Mademoiselle Chambon is a 2009 French romantic drama film directed by Stéphane Brizé, adapted from Eric Holder’s novel, about a married construction worker who falls in love with his son’s schoolteacher.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chère Triple: [Vilaine, tributary, Chère]
Generated description
Chère is a river in western France that flows through the Brittany region before joining the Vilaine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chère Target entity description: Chère is a river in western France that flows through the Brittany region before joining the Vilaine.
-
A.
Pécharmant
Pécharmant is a French wine appellation in southwest France known for its robust, age-worthy red wines made primarily from Bordeaux grape varieties.
-
B.
Charmes
Charmes is a 1922 poetry collection by French symbolist writer Paul Valéry, noted for its intricate, musical verse and philosophical depth.
-
C.
Clémentine
Clémentine is a feminine given name of French origin, commonly used in Francophone countries and beyond.
-
D.
Valentinoise
Valentinoise is the French demonym referring to a female inhabitant of the city of Valence in the Drôme department.
-
E.
Mademoiselle Chambon
Mademoiselle Chambon is a 2009 French romantic drama film directed by Stéphane Brizé, adapted from Eric Holder’s novel, about a married construction worker who falls in love with his son’s schoolteacher.
- F. None of above. chosen
Provenance (5 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f1490881908673f429e5288c86 |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8abde0308190819da6867e703ea7 |
completed | May 8, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_69fd8bb3c1188190b158d30e9c962911 |
completed | May 8, 2026, 7:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd8c6e7d448190835f87e27c998623 |
completed | May 8, 2026, 7:10 a.m. |
Created at: April 10, 2026, 1:23 a.m.