Triple
T778594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bristol |
E16444
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Porto |
E95974
|
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: Porto | Statement: [Bristol, twinnedWith, Porto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Porto Context triple: [Bristol, twinnedWith, Porto]
-
A.
Porto
chosen
Porto is Portugal’s second-largest city, renowned for its historic riverside district, rich maritime heritage, and production of port wine.
-
B.
Lisbon
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.
-
C.
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.
-
D.
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.
-
E.
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.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a74f886081909c27b786e3adbe32 |
completed | March 1, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf4d769c81909eba6cefb241d417 |
completed | March 4, 2026, 6:21 a.m. |
Created at: March 1, 2026, 7:37 p.m.