Triple
T12755011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trianon–MASP |
E304834
|
entity |
| Predicate | adjacentStationOnLine2 |
P81819
|
FINISHED |
| Object |
Brigadeiro
Brigadeiro is an underground metro station on Line 2 (Green) of the São Paulo Metro, serving the busy Avenida Paulista area.
|
E1000215
|
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: Brigadeiro | Statement: [Trianon–MASP, adjacentStationOnLine2, Brigadeiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brigadeiro Context triple: [Trianon–MASP, adjacentStationOnLine2, Brigadeiro]
-
A.
Brigadeiro 356
Brigadeiro 356 was a Soviet-built naval vessel later known as the MV Captain Keith Tibbetts, now a popular Caribbean shipwreck dive site.
-
B.
Caramelo
"Caramelo" is a popular reggaeton/Latin urban hit song by Puerto Rican singer Ozuna, known for its catchy melody and romantic lyrics.
-
C.
Caramelo
Caramelo is a novel by Sandra Cisneros that explores a Mexican American family’s history, identity, and intergenerational relationships through the memories tied to a cherished rebozo (shawl).
-
D.
Chocina
Chocina is a river in northern Poland that serves as a tributary of the Brda River.
-
E.
Brasileirinho
"Brasileirinho" is a famous and virtuosic Brazilian choro composition, widely regarded as a classic of the genre and a showcase for instrumental skill.
- 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: Brigadeiro Triple: [Trianon–MASP, adjacentStationOnLine2, Brigadeiro]
Generated description
Brigadeiro is an underground metro station on Line 2 (Green) of the São Paulo Metro, serving the busy Avenida Paulista area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brigadeiro Target entity description: Brigadeiro is an underground metro station on Line 2 (Green) of the São Paulo Metro, serving the busy Avenida Paulista area.
-
A.
Brigadeiro 356
Brigadeiro 356 was a Soviet-built naval vessel later known as the MV Captain Keith Tibbetts, now a popular Caribbean shipwreck dive site.
-
B.
Caramelo
"Caramelo" is a popular reggaeton/Latin urban hit song by Puerto Rican singer Ozuna, known for its catchy melody and romantic lyrics.
-
C.
Caramelo
Caramelo is a novel by Sandra Cisneros that explores a Mexican American family’s history, identity, and intergenerational relationships through the memories tied to a cherished rebozo (shawl).
-
D.
Chocina
Chocina is a river in northern Poland that serves as a tributary of the Brda River.
-
E.
Brasileirinho
"Brasileirinho" is a famous and virtuosic Brazilian choro composition, widely regarded as a classic of the genre and a showcase for instrumental skill.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c9aa6308190bfcb1511a561c0f9 |
completed | May 2, 2026, 10:37 p.m. |
| NEDg | Description generation | batch_69f67db631348190812ba3582f1850c4 |
completed | May 2, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67ec570a881909c98471b701999f0 |
completed | May 2, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:27 p.m.