Triple
T4939404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saintes-Maries-de-la-Mer |
E110889
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object |
Saintois
A Saintois is a resident or native of the coastal commune of Saintes-Maries-de-la-Mer in southern France.
|
E509203
|
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: Saintois | Statement: [Saintes-Maries-de-la-Mer, hasDemonym, Saintois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saintois Context triple: [Saintes-Maries-de-la-Mer, hasDemonym, Saintois]
-
A.
Saint-Brais
Saint-Brais is a small rural municipality in the canton of Jura in northwestern Switzerland, situated in the Franches-Montagnes district.
-
B.
Soignies
Soignies is a historic town and municipality in the province of Hainaut in Wallonia, Belgium, known for its medieval collegiate church and blue limestone industry.
-
C.
Boussy-Saint-Antoine
Boussy-Saint-Antoine is a suburban commune in the Essonne department in the Île-de-France region of northern France.
-
D.
Brière
Brière is a French-language surname most prominently associated with former NHL player and current hockey executive Daniel Brière.
-
E.
Bresse
Bresse is a historical region in eastern France known for its rich agricultural land, distinctive culinary traditions, and cultural ties to the Franco-Provençal linguistic area.
- 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: Saintois Triple: [Saintes-Maries-de-la-Mer, hasDemonym, Saintois]
Generated description
A Saintois is a resident or native of the coastal commune of Saintes-Maries-de-la-Mer in southern France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saintois Target entity description: A Saintois is a resident or native of the coastal commune of Saintes-Maries-de-la-Mer in southern France.
-
A.
Saint-Brais
Saint-Brais is a small rural municipality in the canton of Jura in northwestern Switzerland, situated in the Franches-Montagnes district.
-
B.
Soignies
Soignies is a historic town and municipality in the province of Hainaut in Wallonia, Belgium, known for its medieval collegiate church and blue limestone industry.
-
C.
Boussy-Saint-Antoine
Boussy-Saint-Antoine is a suburban commune in the Essonne department in the Île-de-France region of northern France.
-
D.
Brière
Brière is a French-language surname most prominently associated with former NHL player and current hockey executive Daniel Brière.
-
E.
Bresse
Bresse is a historical region in eastern France known for its rich agricultural land, distinctive culinary traditions, and cultural ties to the Franco-Provençal linguistic area.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7088f6e48190bf09e58ab053a4d1 |
completed | March 20, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06982c5081908c275019c5d6b1c1 |
completed | March 21, 2026, 8:59 p.m. |
| NEDg | Description generation | batch_69bf09b664948190bebee9c43975e359 |
completed | March 21, 2026, 9:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf0a074da88190b52d2519d66b9f5d |
completed | March 21, 2026, 9:13 p.m. |
Created at: March 20, 2026, 1:31 p.m.