Triple
T12396635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Saint-Nazaire |
E296132
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Besné
Besné is a small French commune located in the Loire-Atlantique department in western France.
|
E983885
|
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: Besné | Statement: [arrondissement of Saint-Nazaire, contains, Besné]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Besné Context triple: [arrondissement of Saint-Nazaire, contains, Besné]
-
A.
Boissonnas
Boissonnas is a Swiss family name notably associated with the renowned photographer Frédéric Boissonnas and his influential work in early 20th-century landscape and travel photography.
-
B.
Bessans
Bessans is a high-altitude village and ski resort in the French Alps known for its Nordic skiing and mountain landscapes.
-
C.
Boulzane
Boulzane is a river in southern France that serves as a tributary of the Agly.
-
D.
Malaucène
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
-
E.
Bezannes
Bezannes is a commune in northeastern France near Reims, known for hosting the Champagne-Ardenne TGV high-speed railway station.
- 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: Besné Triple: [arrondissement of Saint-Nazaire, contains, Besné]
Generated description
Besné is a small French commune located in the Loire-Atlantique department in western France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Besné Target entity description: Besné is a small French commune located in the Loire-Atlantique department in western France.
-
A.
Boissonnas
Boissonnas is a Swiss family name notably associated with the renowned photographer Frédéric Boissonnas and his influential work in early 20th-century landscape and travel photography.
-
B.
Bessans
Bessans is a high-altitude village and ski resort in the French Alps known for its Nordic skiing and mountain landscapes.
-
C.
Boulzane
Boulzane is a river in southern France that serves as a tributary of the Agly.
-
D.
Malaucène
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
-
E.
Bezannes
Bezannes is a commune in northeastern France near Reims, known for hosting the Champagne-Ardenne TGV high-speed railway station.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd33f048190b205fd21dc513f6a |
completed | April 10, 2026, 6:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63efa1520819093cdf6ab3025ab20 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f640ef7dd08190bf78d04cffac1a44 |
completed | May 2, 2026, 6:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f641abe114819093d99a327f2220c2 |
completed | May 2, 2026, 6:25 p.m. |
Created at: April 8, 2026, 9:54 p.m.