Triple
T8138358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corky Gonzales |
E190027
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gonzales |
E163720
|
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: Gonzales | Statement: [Corky Gonzales, familyName, Gonzales]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gonzales Context triple: [Corky Gonzales, familyName, Gonzales]
-
A.
Gonzales
chosen
Gonzales is a Spanish-origin surname common in the United States and Latin America, borne by numerous notable figures in politics, sports, and the arts.
-
B.
Gonsalez
Gonsalez is one of the central vigilante protagonists in Edgar Wallace’s classic crime thriller series "The Four Just Men."
-
C.
Pruitt Herrera
Pruitt Herrera is a central firefighter character and former captain on the television drama series "Station 19."
-
D.
Menéndez
Menéndez is a Spanish-origin surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
-
E.
Lujan
Lujan is a Spanish-origin surname notably associated with American politician Manuel Lujan Jr.
- 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_69ca82bd9900819099477cdc2eb4244f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4402b35c81909363ffa9ce952ca4 |
completed | March 31, 2026, 3:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc949d9c7c81908efb4880f9250166 |
completed | April 1, 2026, 3:44 a.m. |
Created at: March 30, 2026, 5:35 p.m.