Triple
T8409420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rías Altas |
E198583
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Viveiro
Viveiro is a coastal town and municipality in the province of Lugo, Galicia, Spain, known for its historic old quarter and scenic location on the Cantabrian Sea.
|
E731465
|
NE FINISHED |
How this triple was built (4 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: Viveiro | Statement: [Rías Altas, contains, Viveiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viveiro Context triple: [Rías Altas, contains, Viveiro]
-
A.
Cieneguilla
Cieneguilla is a semi-rural district in the eastern part of Lima, Peru, known for its natural landscapes, country houses, and outdoor recreation areas.
-
B.
Varela
Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
-
C.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
-
D.
Moura
Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
-
E.
Vegueta
Vegueta is the historic old quarter of Las Palmas de Gran Canaria, known for its colonial architecture, cobbled streets, and cultural landmarks.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Viveiro Triple: [Rías Altas, contains, Viveiro]
Generated description
Viveiro is a coastal town and municipality in the province of Lugo, Galicia, Spain, known for its historic old quarter and scenic location on the Cantabrian Sea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Viveiro Target entity description: Viveiro is a coastal town and municipality in the province of Lugo, Galicia, Spain, known for its historic old quarter and scenic location on the Cantabrian Sea.
-
A.
Cieneguilla
Cieneguilla is a semi-rural district in the eastern part of Lima, Peru, known for its natural landscapes, country houses, and outdoor recreation areas.
-
B.
Varela
Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
-
C.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
-
D.
Moura
Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
-
E.
Vegueta
Vegueta is the historic old quarter of Las Palmas de Gran Canaria, known for its colonial architecture, cobbled streets, and cultural landmarks.
- F. None of above. chosen
Provenance (5 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb8317045c8190b69cc99854b633be |
completed | March 31, 2026, 8:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce030dccf08190a70c0abf0bdcf244 |
completed | April 2, 2026, 5:47 a.m. |
| NEDg | Description generation | batch_69ce07808098819087e896b87320aefd |
completed | April 2, 2026, 6:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce08759e1c81909c96caf3b571e1ca |
completed | April 2, 2026, 6:11 a.m. |
Created at: March 30, 2026, 6:05 p.m.