Triple
T17600321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Saint-Affrique |
E428680
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Camarès
Camarès is a small commune in the Aveyron department of southern France, known for its rural landscape and traditional Occitan heritage.
|
E1278274
|
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: Camarès | Statement: [canton of Saint-Affrique, contains, Camarès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camarès Context triple: [canton of Saint-Affrique, contains, Camarès]
-
A.
Cazères
Cazères is a small commune in southwestern France situated in the Haute-Garonne department, known for its location along the Garonne River.
-
B.
Nogaro
Nogaro is a small commune in southwestern France’s Gers department, known for its motor racing circuit and Armagnac-producing countryside.
-
C.
Pézenas
Pézenas is a historic town in southern France’s Hérault department, known for its well-preserved medieval center and association with figures like Molière and the Prince de Conti.
-
D.
Leucate
Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
-
E.
Argelès-sur-Mer
Argelès-sur-Mer is a coastal resort town in southern France known for its long Mediterranean beaches and proximity to the Pyrenees.
- 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: Camarès Triple: [canton of Saint-Affrique, contains, Camarès]
Generated description
Camarès is a small commune in the Aveyron department of southern France, known for its rural landscape and traditional Occitan heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Camarès Target entity description: Camarès is a small commune in the Aveyron department of southern France, known for its rural landscape and traditional Occitan heritage.
-
A.
Cazères
Cazères is a small commune in southwestern France situated in the Haute-Garonne department, known for its location along the Garonne River.
-
B.
Nogaro
Nogaro is a small commune in southwestern France’s Gers department, known for its motor racing circuit and Armagnac-producing countryside.
-
C.
Pézenas
Pézenas is a historic town in southern France’s Hérault department, known for its well-preserved medieval center and association with figures like Molière and the Prince de Conti.
-
D.
Leucate
Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
-
E.
Argelès-sur-Mer
Argelès-sur-Mer is a coastal resort town in southern France known for its long Mediterranean beaches and proximity to the Pyrenees.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46c4812d48190bf8e899fa8f7fbe4 |
completed | April 19, 2026, 5:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01e81b951c81908969e6d2f952efc4 |
completed | May 11, 2026, 2:30 p.m. |
| NEDg | Description generation | batch_6a01ef0a9fb48190ac9d38f027ceb728 |
completed | May 11, 2026, 3 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01ef87c62c8190b9a3cd936542d7b4 |
completed | May 11, 2026, 3:02 p.m. |
Created at: April 10, 2026, 5:51 a.m.