Triple
T2263744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle Creek |
E50095
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object |
Santo André
Santo André is a major industrial and residential city in the São Paulo metropolitan region of Brazil.
|
E251826
|
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: Santo André | Statement: [Battle Creek, hasSisterCity, Santo André]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santo André Context triple: [Battle Creek, hasSisterCity, Santo André]
-
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.
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.
São Gonçalo
São Gonçalo is a large municipality in the state of Rio de Janeiro, Brazil, forming part of the metropolitan area of Rio de Janeiro and known for its dense urban character and industrial activity.
-
D.
Ribeirão Preto
Ribeirão Preto is a major city in the state of São Paulo, Brazil, known as an important economic and cultural center with a strong agribusiness and services sector.
-
E.
São Paulo
São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
- 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: Santo André Triple: [Battle Creek, hasSisterCity, Santo André]
Generated description
Santo André is a major industrial and residential city in the São Paulo metropolitan region of Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santo André Target entity description: Santo André is a major industrial and residential city in the São Paulo metropolitan region of Brazil.
-
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.
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.
São Gonçalo
São Gonçalo is a large municipality in the state of Rio de Janeiro, Brazil, forming part of the metropolitan area of Rio de Janeiro and known for its dense urban character and industrial activity.
-
D.
Ribeirão Preto
Ribeirão Preto is a major city in the state of São Paulo, Brazil, known as an important economic and cultural center with a strong agribusiness and services sector.
-
E.
São Paulo
São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18d7fc08190851765683d1b8092 |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71cfd3b08190988474aa0fa985fe |
completed | March 9, 2026, 7:08 a.m. |
| NEDg | Description generation | batch_69ae7688583c8190abb05be41103762a |
completed | March 9, 2026, 7:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae76ec3c0c8190bfb7d25b435c777f |
completed | March 9, 2026, 7:29 a.m. |
Created at: March 4, 2026, 7:48 p.m.