Triple
T17600320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Saint-Affrique |
E428680
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Brusque
Brusque is a small rural commune in southern France, located in the Aveyron department within the Occitanie region.
|
E1278273
|
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: Brusque | Statement: [canton of Saint-Affrique, contains, Brusque]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brusque Context triple: [canton of Saint-Affrique, contains, Brusque]
-
A.
Brusque
Brusque is a city in the Brazilian state of Santa Catarina known for its strong German-Brazilian heritage and textile industry.
-
B.
São Bento do Sul
São Bento do Sul is a municipality in the state of Santa Catarina, Brazil, known for its strong German cultural heritage and furniture industry.
-
C.
Jaraguá do Sul
Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
-
D.
Duas Barras
Duas Barras is a small municipality in the mountainous interior of Rio de Janeiro state in southeastern Brazil.
-
E.
Itajaí
Itajaí is a coastal city in the Brazilian state of Santa Catarina known for its strong German-Brazilian cultural heritage and important Atlantic port.
- 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: Brusque Triple: [canton of Saint-Affrique, contains, Brusque]
Generated description
Brusque is a small rural commune in southern France, located in the Aveyron department within the Occitanie region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brusque Target entity description: Brusque is a small rural commune in southern France, located in the Aveyron department within the Occitanie region.
-
A.
Brusque
Brusque is a city in the Brazilian state of Santa Catarina known for its strong German-Brazilian heritage and textile industry.
-
B.
São Bento do Sul
São Bento do Sul is a municipality in the state of Santa Catarina, Brazil, known for its strong German cultural heritage and furniture industry.
-
C.
Jaraguá do Sul
Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
-
D.
Duas Barras
Duas Barras is a small municipality in the mountainous interior of Rio de Janeiro state in southeastern Brazil.
-
E.
Itajaí
Itajaí is a coastal city in the Brazilian state of Santa Catarina known for its strong German-Brazilian cultural heritage and important Atlantic port.
- 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.