Triple
T20215359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manuel Tagüeña |
E493606
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Tagüeña |
—
|
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: Tagüeña | Statement: [Manuel Tagüeña, familyName, Tagüeña]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tagüeña Context triple: [Manuel Tagüeña, familyName, Tagüeña]
-
A.
Tagüeña
chosen
Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
-
B.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
C.
Bañuela
Bañuela is the highest peak in Spain’s Sierra Morena mountain range, located in the southern part of the Iberian Peninsula.
-
D.
Botorrita
Botorrita is a municipality in the province of Zaragoza, Spain, best known for the discovery of ancient Celtiberian bronze inscriptions found there.
-
E.
Tasqueña
Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ed8cc8c8190889ecadc702010d8 |
completed | April 20, 2026, 6:22 p.m. |
Created at: April 11, 2026, 11:38 p.m.