Triple
T17722587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valgrisenche |
E442377
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Usellières
Usellières is a small alpine settlement in the Valgrisenche valley of Italy’s Aosta region, known as a starting point for mountain hikes and outdoor activities.
|
E1283388
|
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: Usellières | Statement: [Valgrisenche, hasSettlement, Usellières]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Usellières Context triple: [Valgrisenche, hasSettlement, Usellières]
-
A.
Eygalières
Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
-
B.
Rigny-Ussé
Rigny-Ussé is a small commune in central France best known for hosting the fairy-tale Château d’Ussé, said to have inspired Charles Perrault’s “Sleeping Beauty.”
-
C.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
D.
Assencières
Assencières is a small commune in the Aube department of north-central France.
-
E.
Casseneuil
Casseneuil is a small commune in southwestern France, located in the Lot-et-Garonne department in the Nouvelle-Aquitaine region.
- 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: Usellières Triple: [Valgrisenche, hasSettlement, Usellières]
Generated description
Usellières is a small alpine settlement in the Valgrisenche valley of Italy’s Aosta region, known as a starting point for mountain hikes and outdoor activities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Usellières Target entity description: Usellières is a small alpine settlement in the Valgrisenche valley of Italy’s Aosta region, known as a starting point for mountain hikes and outdoor activities.
-
A.
Eygalières
Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
-
B.
Rigny-Ussé
Rigny-Ussé is a small commune in central France best known for hosting the fairy-tale Château d’Ussé, said to have inspired Charles Perrault’s “Sleeping Beauty.”
-
C.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
D.
Assencières
Assencières is a small commune in the Aube department of north-central France.
-
E.
Casseneuil
Casseneuil is a small commune in southwestern France, located in the Lot-et-Garonne department in the Nouvelle-Aquitaine region.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47487b4988190b14237a4e6376e9a |
completed | April 19, 2026, 6:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0230300f548190b9e3bdb6570446ff |
completed | May 11, 2026, 7:38 p.m. |
| NEDg | Description generation | batch_6a02315558cc8190829599a78de8eee2 |
completed | May 11, 2026, 7:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0231e54c308190af6f80f42848536d |
completed | May 11, 2026, 7:45 p.m. |
Created at: April 10, 2026, 10:07 a.m.