Triple
T2720358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State of São Paulo |
E60066
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Jundiaí
Jundiaí is a mid-sized industrial and logistics city in southeastern Brazil known for its strong economy and high quality of life.
|
E318450
|
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: Jundiaí | Statement: [State of São Paulo, hasCity, Jundiaí]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jundiaí Context triple: [State of São Paulo, hasCity, Jundiaí]
-
A.
Jaraguá do Sul
Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
-
B.
Campinas
Campinas is a major city in the state of São Paulo, Brazil, known as an important industrial, technological, and transportation hub in the country.
-
C.
Guarulhos
Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
-
D.
Sorocaba
Sorocaba is a major industrial and commercial city in southeastern Brazil, located in the interior of the state of São Paulo.
-
E.
Piracicaba
Piracicaba is a city in the state of São Paulo, Brazil, known for its strong agricultural and industrial economy and as a regional educational center.
- 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: Jundiaí Triple: [State of São Paulo, hasCity, Jundiaí]
Generated description
Jundiaí is a mid-sized industrial and logistics city in southeastern Brazil known for its strong economy and high quality of life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jundiaí Target entity description: Jundiaí is a mid-sized industrial and logistics city in southeastern Brazil known for its strong economy and high quality of life.
-
A.
Jaraguá do Sul
Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
-
B.
Campinas
Campinas is a major city in the state of São Paulo, Brazil, known as an important industrial, technological, and transportation hub in the country.
-
C.
Guarulhos
Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
-
D.
Sorocaba
Sorocaba is a major industrial and commercial city in southeastern Brazil, located in the interior of the state of São Paulo.
-
E.
Piracicaba
Piracicaba is a city in the state of São Paulo, Brazil, known for its strong agricultural and industrial economy and as a regional educational center.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdab06d388190acf690787fe58ab5 |
completed | March 7, 2026, 7:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12dfe893c81909c79ea6cffb5bae6 |
completed | March 11, 2026, 8:55 a.m. |
| NEDg | Description generation | batch_69b12f07ec088190a63e30f8a1f7937a |
completed | March 11, 2026, 8:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1cb6571388190970bae846bfc57a2 |
completed | March 11, 2026, 8:07 p.m. |
Created at: March 6, 2026, 9:55 p.m.