Triple
T6091629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | García |
E135778
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Garcia |
E135778
|
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: Garcia | Statement: [García, hasVariant, Garcia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garcia Context triple: [García, hasVariant, Garcia]
-
A.
García
chosen
García is a common Spanish surname borne by numerous notable figures across the Spanish-speaking world.
-
B.
Gutiérrez
Gutiérrez is a common Spanish-language surname borne by numerous individuals across the Spanish-speaking world.
-
C.
Garza
Garza is a Spanish-language surname of Basque origin that is common in Mexico and among people of Hispanic heritage.
-
D.
González
González is a common Spanish-language surname widely borne across Spain and Latin America, often associated with Iberian heritage.
-
E.
Herrera
Herrera is a common Spanish surname borne by numerous notable figures across sports, politics, arts, and other fields in the Spanish-speaking world.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057ab7324819086d4708e6f9391c0 |
completed | March 22, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c12531d764819083e1bb37d8c81a6c |
completed | March 23, 2026, 11:34 a.m. |
Created at: March 22, 2026, 4:12 p.m.