Triple
T11894020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 15–Silver |
E282989
|
entity |
| Predicate | station |
P726
|
FINISHED |
| Object |
São Lucas
São Lucas is a metro station on São Paulo’s Line 15–Silver monorail system in Brazil.
|
E952244
|
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 Lucas | Statement: [Line 15–Silver, station, São Lucas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: São Lucas Context triple: [Line 15–Silver, station, São Lucas]
-
A.
Estevão
Estevão is the Portuguese given name equivalent to the Hungarian name István, commonly rendered in English as Stephen.
-
B.
Damião
Damião is a Portuguese given name, equivalent to Damian, commonly used in Lusophone countries.
-
C.
Sebastião
Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
-
D.
Manoel
Manoel is a given name, commonly used in Portuguese- and Spanish-speaking cultures, that is a variant of the name Emmanuel.
-
E.
Paulo
Paulo is a given name most notably associated with Brazilian educator and philosopher Paulo Freire, a leading figure in critical pedagogy.
- 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 Lucas Triple: [Line 15–Silver, station, São Lucas]
Generated description
São Lucas is a metro station on São Paulo’s Line 15–Silver monorail system in Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: São Lucas Target entity description: São Lucas is a metro station on São Paulo’s Line 15–Silver monorail system in Brazil.
-
A.
Estevão
Estevão is the Portuguese given name equivalent to the Hungarian name István, commonly rendered in English as Stephen.
-
B.
Damião
Damião is a Portuguese given name, equivalent to Damian, commonly used in Lusophone countries.
-
C.
Sebastião
Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
-
D.
Manoel
Manoel is a given name, commonly used in Portuguese- and Spanish-speaking cultures, that is a variant of the name Emmanuel.
-
E.
Paulo
Paulo is a given name most notably associated with Brazilian educator and philosopher Paulo Freire, a leading figure in critical pedagogy.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1172988190a2c13d37220f2f93 |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4180569ac81909137d56374e800c0 |
completed | May 1, 2026, 3:03 a.m. |
| NEDg | Description generation | batch_69f41f1abaa481908b8a6873a07af848 |
completed | May 1, 2026, 3:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f42283c4cc81909793834ef65d2514 |
completed | May 1, 2026, 3:48 a.m. |
Created at: April 8, 2026, 9:44 p.m.