Triple
T15967492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villebrune |
E387231
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object |
Villebrune
Villebrune is a personal name that can function as both a given name and a surname, likely of French origin.
|
E1251410
|
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: Villebrune | Statement: [Villebrune, hasGivenName, Villebrune]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Villebrune Context triple: [Villebrune, hasGivenName, Villebrune]
-
A.
Ferrière
Ferrière is a French-language surname of Swiss origin borne by various notable individuals, including social worker and humanitarian Suzanne Ferrière.
-
B.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
C.
Vaugier
Vaugier is the surname of Emmanuelle Vaugier, a Canadian actress and model known for roles in television series such as "Two and a Half Men" and "Smallville."
-
D.
Roquebillière
Roquebillière is a small commune in southeastern France, situated in the Alpes-Maritimes department in the Provence-Alpes-Côte d’Azur region.
-
E.
Laveissière
Laveissière is a small commune in the Cantal department of south-central France, situated in the mountainous Auvergne 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: Villebrune Triple: [Villebrune, hasGivenName, Villebrune]
Generated description
Villebrune is a personal name that can function as both a given name and a surname, likely of French origin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Villebrune Target entity description: Villebrune is a personal name that can function as both a given name and a surname, likely of French origin.
-
A.
Ferrière
Ferrière is a French-language surname of Swiss origin borne by various notable individuals, including social worker and humanitarian Suzanne Ferrière.
-
B.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
C.
Vaugier
Vaugier is the surname of Emmanuelle Vaugier, a Canadian actress and model known for roles in television series such as "Two and a Half Men" and "Smallville."
-
D.
Roquebillière
Roquebillière is a small commune in southeastern France, situated in the Alpes-Maritimes department in the Provence-Alpes-Côte d’Azur region.
-
E.
Laveissière
Laveissière is a small commune in the Cantal department of south-central France, situated in the mountainous Auvergne 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157277e7881908d49f4874766b3b5 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139e380bc81908452f6e8666f23ad |
completed | May 11, 2026, 2:07 a.m. |
| NEDg | Description generation | batch_6a013c9808ec8190af5f0e61e797e63b |
completed | May 11, 2026, 2:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a013d1576548190ae1f218a9a7960cc |
completed | May 11, 2026, 2:21 a.m. |
Created at: April 10, 2026, 4:54 a.m.