Triple
T1852380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipality of Lagoa |
E41623
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Lagoa (city) |
E146783
|
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: Lagoa (city) | Statement: [Municipality of Lagoa, containsSettlement, Lagoa (city)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lagoa (city) Context triple: [Municipality of Lagoa, containsSettlement, Lagoa (city)]
-
A.
Municipality of Lagoa
The Municipality of Lagoa is a coastal local government area in Portugal’s Algarve region, known for its beaches, cliffs, and tourism-centered economy.
-
B.
Lagoa
chosen
Lagoa is a town and municipality in Portugal’s Algarve region, known for its coastal scenery, beaches, and wine production.
-
C.
Cumbuco
Cumbuco is a coastal village in northeastern Brazil known for its sand dunes, lagoons, and strong winds that make it a popular destination for kitesurfing and other beach tourism.
-
D.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
E.
Afogados
Afogados is a populous neighborhood in the Brazilian city of Recife, known for its busy commercial areas and dense urban character.
- 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb06999f4819086386aafb789a368 |
completed | March 7, 2026, 4:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1c6941081909cef987ebe4b4d6c |
completed | March 8, 2026, 7:45 p.m. |
Created at: March 4, 2026, 7:33 p.m.