Triple
T10165359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gustavo Gutiérrez |
E235192
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gutiérrez |
E195978
|
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: Gutiérrez | Statement: [Gustavo Gutiérrez, familyName, Gutiérrez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gutiérrez Context triple: [Gustavo Gutiérrez, familyName, Gutiérrez]
-
A.
Gutiérrez
chosen
Gutiérrez is a common Spanish-language surname borne by numerous individuals across the Spanish-speaking world.
-
B.
González
González is a common Spanish-language surname widely borne across Spain and Latin America, often associated with Iberian heritage.
-
C.
Covarrubias
Covarrubias is a Spanish surname most notably associated with Renaissance architect and sculptor Alonso de Covarrubias, whose work significantly shaped the Plateresque style.
-
D.
Herrera
Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
-
E.
Martínez
Martínez is a common Spanish-language surname widely borne across Spain and Latin America.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6b96dc8190ae37d0d28e4c393b |
completed | April 2, 2026, 4:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300d672fc8190ad5b937d02a737fd |
completed | April 6, 2026, 12:39 a.m. |
Created at: March 30, 2026, 9:10 p.m.