Triple
T22996412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | de Castro |
E572205
|
entity |
| Predicate | hasOrthographicVariant |
P457
|
FINISHED |
| Object | deCastro |
—
|
NE NERFINISHED |
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: deCastro | Statement: [de Castro, hasOrthographicVariant, deCastro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: deCastro Context triple: [de Castro, hasOrthographicVariant, deCastro]
-
A.
de Castro
chosen
de Castro is a Portuguese-origin surname borne by numerous notable figures in the arts, politics, and academia across Lusophone countries.
-
B.
del Castillo
Del Castillo is a Spanish-language surname notably borne by Mexican actress Kate del Castillo and other members of her prominent entertainment family.
-
C.
Castro Daire
Castro Daire is a municipality in Portugal’s Viseu District, known for its mountainous landscapes, thermal springs, and location along key interior transport routes.
-
D.
del Pilar
del Pilar is a Filipino surname notably borne by several prominent figures in Philippine history and culture.
-
E.
Dela Cruz
Dela Cruz is a common Spanish-derived surname, especially prevalent in the Philippines and other Spanish-influenced countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f3186c81909e0d5177029a72ae |
completed | April 29, 2026, 4:02 a.m. |
Created at: April 17, 2026, 3:50 p.m.