Triple
T4298571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hautes-Alpes |
E99775
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Serre-Chevalier
Serre-Chevalier is a major ski resort in the French Alps, renowned for its extensive slopes, sunny climate, and traditional mountain villages.
|
E429935
|
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: Serre-Chevalier | Statement: [Hautes-Alpes, contains, Serre-Chevalier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serre-Chevalier Context triple: [Hautes-Alpes, contains, Serre-Chevalier]
-
A.
Guignard
Guignard was a prominent Brazilian painter and art educator known for his lyrical landscapes and significant influence on modern Brazilian art.
-
B.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
-
C.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
D.
Masson-Angers
Masson-Angers is a former municipality in western Quebec, Canada, that now forms a sector within the city of Gatineau.
-
E.
Doussard
Doussard is a French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region, known for its scenic setting at the southern end of Lake Annecy and its outdoor recreational activities.
- 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: Serre-Chevalier Triple: [Hautes-Alpes, contains, Serre-Chevalier]
Generated description
Serre-Chevalier is a major ski resort in the French Alps, renowned for its extensive slopes, sunny climate, and traditional mountain villages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Serre-Chevalier Target entity description: Serre-Chevalier is a major ski resort in the French Alps, renowned for its extensive slopes, sunny climate, and traditional mountain villages.
-
A.
Guignard
Guignard was a prominent Brazilian painter and art educator known for his lyrical landscapes and significant influence on modern Brazilian art.
-
B.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
-
C.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
D.
Masson-Angers
Masson-Angers is a former municipality in western Quebec, Canada, that now forms a sector within the city of Gatineau.
-
E.
Doussard
Doussard is a French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region, known for its scenic setting at the southern end of Lake Annecy and its outdoor recreational activities.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509d39348190aa83304661230cba |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c746c9108190a1a81e94b4768f3c |
completed | March 14, 2026, 8:38 p.m. |
| NEDg | Description generation | batch_69b5c929aec48190bb9a00b7086afe01 |
completed | March 14, 2026, 8:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5c993a9388190a52e573b013dbe29 |
completed | March 14, 2026, 8:48 p.m. |
Created at: March 12, 2026, 11:08 p.m.