Triple
T1321479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anton |
E28227
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Antón |
E36235
|
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: Antón | Statement: [Anton, hasVariant, Antón]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antón Context triple: [Anton, hasVariant, Antón]
-
A.
Eugenio
Eugenio is a masculine given name of Greek origin, commonly used in Spanish- and Italian-speaking countries.
-
B.
Pascual
Pascual is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
-
C.
Antonio Trashorras
Antonio Trashorras is a Spanish screenwriter best known for his work in horror cinema, including co-writing Guillermo del Toro’s acclaimed film "The Devil’s Backbone."
-
D.
Antoni
chosen
Antoni is a masculine given name of Latin origin, commonly used in Poland and other European countries.
-
E.
Andrés
Andrés is a Spanish given name commonly used as the equivalent of Andrew.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19932888190a3d45871e84f112e |
completed | March 1, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc6255b808190823bc240365ed304 |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:55 p.m.