Triple
T5116292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Davila |
E115342
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Dávila |
E115342
|
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: Dávila | Statement: [Davila, hasSpellingVariant, Dávila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dávila Context triple: [Davila, hasSpellingVariant, Dávila]
-
A.
Davila
chosen
Davila is an Italian surname most notably associated with the 17th-century historian Enrico Caterino Davila.
-
B.
Balderas
Balderas is a major Mexico City Metro station known for its central location and high passenger traffic.
-
C.
Esquivel
Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
-
D.
Gaspar
Gaspar is the given name of Gaspar de Guzmán, Count-Duke of Olivares, a powerful 17th-century Spanish royal favorite and statesman under King Philip IV.
-
E.
Magaña
Magaña is a Spanish-language surname of Hispanic origin borne by various notable individuals in Mexico and other Spanish-speaking countries.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75cfa9f88190aa7dfd264e554899 |
completed | March 20, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec3758bb4819082d5876c4dc9df8d |
completed | March 21, 2026, 4:12 p.m. |
Created at: March 20, 2026, 1:41 p.m.