Triple
T5774072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tejo |
E127395
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Zêzere |
E132565
|
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: Zêzere | Statement: [Tejo, hasTributary, Zêzere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zêzere Context triple: [Tejo, hasTributary, Zêzere]
-
A.
Zêzere River
chosen
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.
-
B.
Viseu
Viseu is a historic inland city in central Portugal known for its well-preserved medieval center, wine production, and cultural heritage.
-
C.
Rio Maior
Rio Maior is a Portuguese city known for its traditional salt pans and location in the Ribatejo region.
-
D.
Sever do Vouga
Sever do Vouga is a municipality in central Portugal known for its natural landscapes, waterfalls, and rural tourism within the Aveiro District.
-
E.
Ribeira da Torre
Ribeira da Torre is a scenic, steep-sided valley and river gorge on the island of Santo Antão in Cape Verde, known for its dramatic landscapes and terraced agriculture.
- 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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029af681081908276e99c568561ce |
completed | March 22, 2026, 5:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e6bf6348190b0ba46253585c7d9 |
completed | March 22, 2026, 11:42 p.m. |
Created at: March 22, 2026, 3:50 p.m.