Triple
T18582534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mañegu |
E454150
|
entity |
| Predicate | hasDialectalRelationWith |
P10003
|
FINISHED |
| Object | Valverdeñu |
—
|
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: Valverdeñu | Statement: [Mañegu, hasDialectalRelationWith, Valverdeñu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valverdeñu Context triple: [Mañegu, hasDialectalRelationWith, Valverdeñu]
-
A.
Villanúa
Villanúa is a small Pyrenean village in northeastern Spain known for its mountain scenery, outdoor activities, and proximity to the French border.
-
B.
Valdoviño
Valdoviño is a coastal municipality in the province of A Coruña, Galicia, Spain, known for its beaches and scenic Atlantic landscapes.
-
C.
Valverdeiru
chosen
Valverdeiru is a regional dialect of the Fala language spoken in the Valverde del Fresno area of Extremadura, Spain.
-
D.
Churriana
Churriana is a district of Málaga in southern Spain, known for encompassing the area around Málaga–Costa del Sol Airport and lying close to the Mediterranean coast.
-
E.
Coveñas
Coveñas is a coastal municipality and popular beach destination on Colombia’s Caribbean Sea, known for its tourism and oil-related port activities.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543d10b1c8190a401df810b7290c9 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 11:44 a.m.