Triple
T15068498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golegã |
E379815
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Médio Tejo |
E1138027
|
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: Médio Tejo | Statement: [Golegã, locatedIn, Médio Tejo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Médio Tejo Context triple: [Golegã, locatedIn, Médio Tejo]
-
A.
Médio Tejo
chosen
Médio Tejo is an intermunicipal subregion in central Portugal that includes several municipalities such as Alcanena and is known for its mix of historical towns and natural landscapes.
-
B.
Alto Tâmega
Alto Tâmega is an inland subregion of northern Portugal known for its mountainous landscapes, thermal springs, and traditional rural communities.
-
C.
Rio Minho
Rio Minho is the longest river in Jamaica, flowing through the island’s central region before emptying into the Caribbean Sea.
-
D.
Alto Minho
Alto Minho is a scenic subregion in northern Portugal known for its lush green landscapes, historic towns, and production of Vinho Verde wine.
-
E.
Lezíria do Tejo
Lezíria do Tejo is a fertile agricultural subregion in central Portugal, known for its river plains along the Tagus and its traditional Ribatejo rural culture.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedeebc7e48190a86b4f0afe8844bb |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fec878c52c8190bf010b1fd4d21f65 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 10, 2026, 3:02 a.m.