Triple
T16361541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resende |
E397322
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Resende (town) |
E887108
|
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: Resende (town) | Statement: [Resende, capital, Resende (town)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Resende (town) Context triple: [Resende, capital, Resende (town)]
-
A.
Resende, Rio de Janeiro, Brazil
Resende, in the state of Rio de Janeiro, Brazil, is a municipality known for its industrial sector, military institutions, and location in the Paraíba do Sul valley.
-
B.
Resende
chosen
Resende is a municipality in the state of Rio de Janeiro, Brazil, known as an important industrial and regional center in the southern part of the state.
-
C.
Resende
Resende is a Portuguese municipality in the Douro region, known for its scenic river landscapes and production of cherries and vinho verde.
-
D.
Itaguaí
Itaguaí is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its major port facilities and heavy industrial and logistics activities.
-
E.
Volta Redonda
Volta Redonda is an industrial city in southeastern Brazil best known for its major steel production complex and role in the country’s metallurgical sector.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad304448190b3f6f0350a1e151d |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dbeabe081909e3d02676293e8b2 |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:08 a.m.