Triple
T1271175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salgueiro Maia |
E15711
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Santarem |
E127396
|
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: Santarem | Statement: [Salgueiro Maia, residence, Santarem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santarem Context triple: [Salgueiro Maia, residence, Santarem]
-
A.
Belém
Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
-
B.
Santarém
Santarém is a Brazilian city in the state of Pará, known for its location at the confluence of the Amazon and Tapajós rivers and its striking “meeting of the waters” phenomenon.
-
C.
Santarém
chosen
Santarém is a historic Portuguese city in the Ribatejo region, known for its Gothic architecture and strategic position overlooking the Tagus River.
-
D.
Manaus
Manaus is a major Brazilian city and capital of the state of Amazonas, known as a key gateway to the Amazon rainforest and an important industrial and cultural center in the region.
-
E.
Morada Nova
Morada Nova is a municipality in the state of Ceará in northeastern Brazil, known for its agricultural activities and semi-arid landscape.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c06ae7b88190a1e0b5232d84a7b1 |
completed | March 1, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4005cd4c81909cff0ed6529d1695 |
completed | March 8, 2026, 9:23 a.m. |
Created at: March 1, 2026, 7:50 p.m.