Triple
T14791782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Brioude |
E347671
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object |
Saint-Vert
Saint-Vert is a small commune in south-central France, located in the Haute-Loire department within the Auvergne-Rhône-Alpes region.
|
E1167795
|
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: Saint-Vert | Statement: [Arrondissement of Brioude, containsAdministrativeTerritorialEntity, Saint-Vert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Vert Context triple: [Arrondissement of Brioude, containsAdministrativeTerritorialEntity, Saint-Vert]
-
A.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
-
B.
Montfavet
Montfavet is a district of Avignon in southeastern France, known in part for its psychiatric hospital where sculptor Camille Claudel spent her final years and died.
-
C.
Saint-Véran
Saint-Véran is a French wine appellation in southern Burgundy known for its high-quality Chardonnay-based white wines.
-
D.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
E.
Bellecourt
Bellecourt is a surname most notably associated with Native American activist Vernon Bellecourt.
- 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: Saint-Vert Triple: [Arrondissement of Brioude, containsAdministrativeTerritorialEntity, Saint-Vert]
Generated description
Saint-Vert is a small commune in south-central France, located in the Haute-Loire department within the Auvergne-Rhône-Alpes region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saint-Vert Target entity description: Saint-Vert is a small commune in south-central France, located in the Haute-Loire department within the Auvergne-Rhône-Alpes region.
-
A.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
-
B.
Montfavet
Montfavet is a district of Avignon in southeastern France, known in part for its psychiatric hospital where sculptor Camille Claudel spent her final years and died.
-
C.
Saint-Véran
Saint-Véran is a French wine appellation in southern Burgundy known for its high-quality Chardonnay-based white wines.
-
D.
Verrières
Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
-
E.
Bellecourt
Bellecourt is a surname most notably associated with Native American activist Vernon Bellecourt.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5d134c819080ee788b2e34163a |
completed | April 14, 2026, 11:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f21a97c819082b59b343ef337ec |
completed | May 9, 2026, 4:21 p.m. |
| NEDg | Description generation | batch_69ff609eafb881909eb69307d41ab676 |
completed | May 9, 2026, 4:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff612340748190987e567e43460f62 |
completed | May 9, 2026, 4:30 p.m. |
Created at: April 10, 2026, 1:31 a.m.