Triple
T3110524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vosges Mountains |
E64937
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
La Bresse
La Bresse is a French mountain town in northeastern France known for its ski resort and outdoor activities in the Vosges.
|
E326493
|
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: La Bresse | Statement: [Vosges Mountains, hasTown, La Bresse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Bresse Context triple: [Vosges Mountains, hasTown, La Bresse]
-
A.
Cottévrard
Cottévrard is a small commune in the Seine-Maritime department of the Normandy region in northern France.
-
B.
La Dôle
La Dôle is a prominent mountain peak in the Jura range of western Switzerland, known for its panoramic views over Lake Geneva and the Alps and for hosting telecommunications and weather facilities near its summit.
-
C.
Armançon
Armançon is a river in central-eastern France that flows through the Burgundy region before joining the Yonne River.
-
D.
Vallée de Chaudefour
Vallée de Chaudefour is a protected glacial valley in France’s Massif Central, renowned for its dramatic volcanic landscapes, rich biodiversity, and popular hiking trails.
-
E.
Clessé
Clessé is a wine-producing village in the Mâconnais region of Burgundy, France, known for its quality white wines.
- 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: La Bresse Triple: [Vosges Mountains, hasTown, La Bresse]
Generated description
La Bresse is a French mountain town in northeastern France known for its ski resort and outdoor activities in the Vosges.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Bresse Target entity description: La Bresse is a French mountain town in northeastern France known for its ski resort and outdoor activities in the Vosges.
-
A.
Cottévrard
Cottévrard is a small commune in the Seine-Maritime department of the Normandy region in northern France.
-
B.
La Dôle
La Dôle is a prominent mountain peak in the Jura range of western Switzerland, known for its panoramic views over Lake Geneva and the Alps and for hosting telecommunications and weather facilities near its summit.
-
C.
Armançon
Armançon is a river in central-eastern France that flows through the Burgundy region before joining the Yonne River.
-
D.
Vallée de Chaudefour
Vallée de Chaudefour is a protected glacial valley in France’s Massif Central, renowned for its dramatic volcanic landscapes, rich biodiversity, and popular hiking trails.
-
E.
Clessé
Clessé is a wine-producing village in the Mâconnais region of Burgundy, France, known for its quality white wines.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada437c5e08190af22f6fa11cf9252 |
completed | March 8, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20394a8cc8190b114760079f8b0f6 |
completed | March 12, 2026, 12:06 a.m. |
| NEDg | Description generation | batch_69b2043430548190a538c183aef44b44 |
completed | March 12, 2026, 12:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b204c812f081908fe5733305123c0e |
completed | March 12, 2026, 12:11 a.m. |
Created at: March 8, 2026, 3:04 p.m.