Triple
T10914032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Girons |
E257773
|
entity |
| Predicate | demographicsLabel |
P2263
|
FINISHED |
| Object |
Saint-Gironnais
Saint-Gironnais refers to the inhabitants or natives of the town of Saint-Girons in southwestern France.
|
E894256
|
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-Gironnais | Statement: [Saint-Girons, demographicsLabel, Saint-Gironnais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Gironnais Context triple: [Saint-Girons, demographicsLabel, Saint-Gironnais]
-
A.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
-
B.
Vendômois
Vendômois is the French demonym referring to inhabitants or natives of the town of Vendôme in central France.
-
C.
Ambertois
Ambertois is the French demonym for inhabitants of the town of Ambert in central France.
-
D.
Mâconnais
Mâconnais is a wine-producing subregion in southern Burgundy, France, best known for its Chardonnay-based white wines.
-
E.
Rouergue
Rouergue is a historic cultural region in southern France, centered around the present-day Aveyron department and known for its rural landscapes, medieval towns, and Occitan heritage.
- 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-Gironnais Triple: [Saint-Girons, demographicsLabel, Saint-Gironnais]
Generated description
Saint-Gironnais refers to the inhabitants or natives of the town of Saint-Girons in southwestern France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saint-Gironnais Target entity description: Saint-Gironnais refers to the inhabitants or natives of the town of Saint-Girons in southwestern France.
-
A.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
-
B.
Vendômois
Vendômois is the French demonym referring to inhabitants or natives of the town of Vendôme in central France.
-
C.
Ambertois
Ambertois is the French demonym for inhabitants of the town of Ambert in central France.
-
D.
Mâconnais
Mâconnais is a wine-producing subregion in southern Burgundy, France, best known for its Chardonnay-based white wines.
-
E.
Rouergue
Rouergue is a historic cultural region in southern France, centered around the present-day Aveyron department and known for its rural landscapes, medieval towns, and Occitan heritage.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77073d12881908ea59771b84bc804 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e216eb77dc81908c380f5fcd507275 |
completed | April 17, 2026, 11:18 a.m. |
| NEDg | Description generation | batch_69e21d8952c881908a952de83754e049 |
completed | April 17, 2026, 11:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e2247fbd348190bb0d221923dac892 |
completed | April 17, 2026, 12:16 p.m. |
Created at: April 8, 2026, 9:22 p.m.