Triple
T14574979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariano Abasolo |
E342018
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Abasolo
Abasolo is a Spanish-language surname of Basque origin borne by various notable individuals and families.
|
E1109217
|
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: Abasolo | Statement: [Mariano Abasolo, familyName, Abasolo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abasolo Context triple: [Mariano Abasolo, familyName, Abasolo]
-
A.
Alajeró
Alajeró is a small coastal and rural municipality on the island of La Gomera in Spain’s Canary Islands, known for its rugged landscapes and traditional Canarian character.
-
B.
Requena
Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
-
C.
Requena
Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
-
D.
Andújar
Andújar is a historic town in the province of Jaén, Andalusia, Spain, known for its olive oil production and its location near the Sierra de Andújar Natural Park.
-
E.
Gualba
Gualba is a small municipality in the Vallès Oriental comarca of Catalonia, Spain, known for its natural surroundings near the Montseny Massif.
- 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: Abasolo Triple: [Mariano Abasolo, familyName, Abasolo]
Generated description
Abasolo is a Spanish-language surname of Basque origin borne by various notable individuals and families.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Abasolo Target entity description: Abasolo is a Spanish-language surname of Basque origin borne by various notable individuals and families.
-
A.
Alajeró
Alajeró is a small coastal and rural municipality on the island of La Gomera in Spain’s Canary Islands, known for its rugged landscapes and traditional Canarian character.
-
B.
Requena
Requena is a small Peruvian city in the Loreto region, known as a remote Amazonian river port and gateway to surrounding rainforest communities.
-
C.
Requena
Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
-
D.
Andújar
Andújar is a historic town in the province of Jaén, Andalusia, Spain, known for its olive oil production and its location near the Sierra de Andújar Natural Park.
-
E.
Gualba
Gualba is a small municipality in the Vallès Oriental comarca of Catalonia, Spain, known for its natural surroundings near the Montseny Massif.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f49d58819094fcd2a702e146cb |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94b5d97481908b2d3d531817a3a6 |
completed | May 8, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69fda288eea081909b3f4a202e89d221 |
completed | May 8, 2026, 8:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fda2fac5fc8190a924c296c74fbf14 |
completed | May 8, 2026, 8:46 a.m. |
Created at: April 10, 2026, 1:24 a.m.