Triple
T565811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portuguese Armed Forces |
E13549
|
entity |
| Predicate | garrison |
P75
|
FINISHED |
| Object | Lisbon |
E3151
|
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: Lisbon | Statement: [Portuguese Armed Forces, garrison, Lisbon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisbon Context triple: [Portuguese Armed Forces, garrison, Lisbon]
-
A.
Lisbon
chosen
Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
-
B.
Coimbra
Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
-
C.
Portimão
Portimão is a coastal city and popular tourist destination in southern Portugal, known for its beaches, marina, and vibrant waterfront along the Arade River.
-
D.
Albufeira
Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
-
E.
Ponta Delgada
Ponta Delgada is the largest city and main economic and administrative center of the Azores archipelago in Portugal, located on the island of São Miguel.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a74793481908fee3baff0b1d348 |
completed | March 1, 2026, 7:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5089bce6c8190a5c4f708fb94668b |
completed | March 2, 2026, 3:48 a.m. |
Created at: March 1, 2026, 7:32 p.m.