Triple
T20202810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rua Nova do Carvalho |
E493266
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Rua Cor-de-Rosa |
—
|
NE NERFINISHED |
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: Rua Cor-de-Rosa | Statement: [Rua Nova do Carvalho, alsoKnownAs, Rua Cor-de-Rosa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rua Cor-de-Rosa Context triple: [Rua Nova do Carvalho, alsoKnownAs, Rua Cor-de-Rosa]
-
A.
Rua do Loreto
Rua do Loreto is a historic street in Lisbon’s Bairro Alto/Chiado area, known for its traditional shops, cafés, and central role in the city’s urban life.
-
B.
Rua da Rosa
chosen
Rua da Rosa is a historic street located in central Lisbon, Portugal, known for its traditional architecture and urban charm.
-
C.
Rua Ivens
Rua Ivens is a central street in Lisbon’s historic Baixa district, known for its shops, restaurants, and proximity to major city landmarks.
-
D.
Rua da Madalena
Rua da Madalena is a historic street in Lisbon’s city center, known for its traditional shops and proximity to major downtown landmarks.
-
E.
Rua da Vitória
Rua da Vitória is a historic street in central Lisbon, Portugal, known for its traditional shops and location in the Baixa district.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d8ec73c8190b630599c5ceb22ac |
completed | April 20, 2026, 6:16 p.m. |
Created at: April 11, 2026, 11:37 p.m.