Triple
T18117692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Col du Soulor |
E433649
|
entity |
| Predicate | hasAscentFrom |
P52151
|
FINISHED |
| Object |
Ferrières
Ferrières is a small village in the French Pyrenees, known as a starting point for mountain routes and scenic climbs in the region.
|
E1306809
|
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: Ferrières | Statement: [Col du Soulor, hasAscentFrom, Ferrières]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ferrières Context triple: [Col du Soulor, hasAscentFrom, Ferrières]
-
A.
Ferrières
Ferrières is a municipality in the province of Liège in Wallonia, Belgium, known for its rural character and scenic Ardennes landscapes.
-
B.
Ferrière
Ferrière is a French-language surname of Swiss origin borne by various notable individuals, including social worker and humanitarian Suzanne Ferrière.
-
C.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
D.
Fallières
Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
-
E.
Villeneuve-sur-Fère
Villeneuve-sur-Fère is a small commune in northern France best known as the birthplace of the poet and dramatist Paul Claudel.
- 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: Ferrières Triple: [Col du Soulor, hasAscentFrom, Ferrières]
Generated description
Ferrières is a small village in the French Pyrenees, known as a starting point for mountain routes and scenic climbs in the region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ferrières Target entity description: Ferrières is a small village in the French Pyrenees, known as a starting point for mountain routes and scenic climbs in the region.
-
A.
Ferrières
Ferrières is a municipality in the province of Liège in Wallonia, Belgium, known for its rural character and scenic Ardennes landscapes.
-
B.
Ferrière
Ferrière is a French-language surname of Swiss origin borne by various notable individuals, including social worker and humanitarian Suzanne Ferrière.
-
C.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
D.
Fallières
Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
-
E.
Villeneuve-sur-Fère
Villeneuve-sur-Fère is a small commune in northern France best known as the birthplace of the poet and dramatist Paul Claudel.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd737708190863fba97cdc20d88 |
completed | April 19, 2026, 1:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a037c40b66c819095d90006fa7ecc37 |
completed | May 12, 2026, 7:15 p.m. |
| NEDg | Description generation | batch_6a037d8d2bc081908c23325f016e0a3d |
completed | May 12, 2026, 7:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a037e38eee4819090dc733e4aa7299b |
completed | May 12, 2026, 7:23 p.m. |
Created at: April 10, 2026, 10:28 a.m.