Triple
T11478855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Carlos |
E272089
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Araraquara |
E334472
|
NE FINISHED |
How this triple was built (2 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: Araraquara | Statement: [São Carlos, locatedNear, Araraquara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Araraquara Context triple: [São Carlos, locatedNear, Araraquara]
-
A.
Araraquara
chosen
Araraquara is a mid-sized city in southeastern Brazil known for its agricultural economy, especially sugarcane production, and its role as a regional commercial and educational center.
-
B.
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.
-
C.
Guarujá
Guarujá is a coastal resort city in southeastern Brazil known for its popular beaches and tourism.
-
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.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294f0e948190b2e106beb86e4b2c |
completed | April 9, 2026, 10:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6249ee74881908814cf59c82038a6 |
completed | April 20, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:36 p.m.