Triple
T13364113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linha de Leixões |
E318892
|
entity |
| Predicate | locatedInMunicipality |
P40
|
FINISHED |
| Object | Matosinhos |
E657030
|
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: Matosinhos | Statement: [Linha de Leixões, locatedInMunicipality, Matosinhos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matosinhos Context triple: [Linha de Leixões, locatedInMunicipality, Matosinhos]
-
A.
Matosinhos
chosen
Matosinhos is a coastal city in northern Portugal known for its port, beaches, and seafood cuisine, forming part of the Porto metropolitan area.
-
B.
Seixas
Seixas is a surname most notably associated with individuals of Portuguese and Sephardic Jewish heritage.
-
C.
Santo Tirso
Santo Tirso is a municipality in northern Portugal known for its textile industry, historic monasteries, and location in the Porto metropolitan area.
-
D.
Mosteiros
Mosteiros is a coastal civil parish on the western tip of São Miguel Island in the Azores, known for its volcanic rock formations, natural swimming pools, and scenic Atlantic views.
-
E.
Mosteiros
Mosteiros is a coastal municipality on the island of Fogo in Cape Verde, known for its volcanic landscapes, coffee production, and black-sand beaches.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da628c71ac81908cfa36342077766e |
completed | April 11, 2026, 3:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19226eb881908f76134a04e72548 |
completed | May 7, 2026, 10:58 p.m. |
Created at: April 9, 2026, 9:32 p.m.