Triple
T7049137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gonzales |
E163720
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Gonzalesz |
E546534
|
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: Gonzalesz | Statement: [Gonzales, hasVariant, Gonzalesz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gonzalesz Context triple: [Gonzales, hasVariant, Gonzalesz]
-
A.
González
chosen
González is a common Spanish-language surname widely borne across Spain and Latin America, often associated with Iberian heritage.
-
B.
Godínez
Godínez is a Spanish-language surname of Iberian origin commonly found across Latin America and among Hispanic communities worldwide.
-
C.
Velasco
Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
-
D.
Gonsalez
Gonsalez is one of the central vigilante protagonists in Edgar Wallace’s classic crime thriller series "The Four Just Men."
-
E.
Negrete
Negrete is a small town and commune in Chile’s Biobío Region, known for its rural character and location near the Biobío River.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e24d5e8c8190b37e56107e6da8ab |
completed | March 27, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c794429b648190b6399a2447db07d0 |
completed | March 28, 2026, 8:41 a.m. |
Created at: March 27, 2026, 2:37 p.m.