Triple
T11459864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ana María Huarte de Iturbide |
E271625
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Huarte |
E874540
|
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: Huarte | Statement: [Ana María Huarte de Iturbide, familyName, Huarte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huarte Context triple: [Ana María Huarte de Iturbide, familyName, Huarte]
-
A.
Huarte
chosen
Huarte is a Spanish surname most notably borne by John Huarte, an American football quarterback who won the 1964 Heisman Trophy.
-
B.
Huerta
Huerta is a Spanish-language surname borne by numerous individuals, including notable figures in politics, activism, and the arts.
-
C.
Balazote
Balazote is a municipality in the province of Albacete, Spain, known for its archaeological heritage and rural Castilian-La Mancha setting.
-
D.
Echeandía
Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
-
E.
Azaña
Azaña is the surname of Manuel Azaña, a prominent Spanish politician and writer who served as President of the Second Spanish Republic.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f2138081909408c7916cef99c9 |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e911c03c819081f1447b320dd2f2 |
completed | April 20, 2026, 8:51 a.m. |
Created at: April 8, 2026, 9:35 p.m.