Triple
T10144419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porto District |
E231665
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object | Tâmega River |
E223728
|
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: Tâmega River | Statement: [Porto District, hasRiver, Tâmega River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tâmega River Context triple: [Porto District, hasRiver, Tâmega River]
-
A.
Tâmega River
chosen
The Tâmega River is a significant river in the Iberian Peninsula that flows through northern Portugal and parts of Spain, contributing notably to the Douro River basin.
-
B.
Zêzere River
The Zêzere River is a major river in central Portugal known for its scenic valleys, hydroelectric dams, and role in feeding the Castelo de Bode Reservoir.
-
C.
Cávado River
The Cávado River is a major river in northern Portugal that flows from the Peneda-Gerês mountains to the Atlantic Ocean, passing through the Minho region and supporting local agriculture, hydropower, and tourism.
-
D.
Dão River
The Dão River is a river in central Portugal known for flowing through the Dão wine region before joining the Mondego River.
-
E.
Alto Tâmega
Alto Tâmega is an inland subregion of northern Portugal known for its mountainous landscapes, thermal springs, and traditional rural communities.
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdeb28a1708190b46499dbe51a694a |
completed | April 2, 2026, 4:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3008e56a481908d64077851063dbf |
completed | April 6, 2026, 12:38 a.m. |
Created at: March 30, 2026, 9:07 p.m.