Triple
T13067663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cotia |
E329369
|
entity |
| Predicate | borderingEntity |
P224
|
FINISHED |
| Object |
São Roque
São Roque is a municipality in the state of São Paulo, Brazil, known for its wine production and scenic mountainous landscapes.
|
E1020755
|
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: São Roque | Statement: [Cotia, borderingEntity, São Roque]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: São Roque Context triple: [Cotia, borderingEntity, São Roque]
-
A.
Santo Amaro
Santo Amaro is a central neighborhood in Recife, Brazil, known for its mix of residential areas, commerce, and important urban infrastructure.
-
B.
Barretos
Barretos is a municipality in the Brazilian state of São Paulo, widely known for hosting one of the largest annual rodeo festivals in Latin America.
-
C.
Bauru
Bauru is a city in the state of São Paulo, Brazil, known as a regional economic and educational hub that hosts a campus of the University of São Paulo.
-
D.
Taubaté
Taubaté is a historic industrial and educational city in southeastern Brazil, located in the Paraíba Valley between São Paulo and Rio de Janeiro.
-
E.
São Carlos
São Carlos is a Brazilian city in the state of São Paulo known as a major university and technology hub, hosting important campuses and research centers.
- 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: São Roque Triple: [Cotia, borderingEntity, São Roque]
Generated description
São Roque is a municipality in the state of São Paulo, Brazil, known for its wine production and scenic mountainous landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: São Roque Target entity description: São Roque is a municipality in the state of São Paulo, Brazil, known for its wine production and scenic mountainous landscapes.
-
A.
Santo Amaro
Santo Amaro is a central neighborhood in Recife, Brazil, known for its mix of residential areas, commerce, and important urban infrastructure.
-
B.
Barretos
Barretos is a municipality in the Brazilian state of São Paulo, widely known for hosting one of the largest annual rodeo festivals in Latin America.
-
C.
Bauru
Bauru is a city in the state of São Paulo, Brazil, known as a regional economic and educational hub that hosts a campus of the University of São Paulo.
-
D.
Taubaté
Taubaté is a historic industrial and educational city in southeastern Brazil, located in the Paraíba Valley between São Paulo and Rio de Janeiro.
-
E.
São Carlos
São Carlos is a Brazilian city in the state of São Paulo known as a major university and technology hub, hosting important campuses and research centers.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ec8ba48190baf52c7823482680 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d603419c8190b8d1726365db59dc |
completed | May 3, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69f6d943a80c81909bc39b9a9ef303bd |
completed | May 3, 2026, 5:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6da1e56388190b536831b2c6d493f |
completed | May 3, 2026, 5:16 a.m. |
Created at: April 9, 2026, 9 p.m.