Triple
T4817679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marquis de Casalduero |
E107627
|
entity |
| Predicate | languageOfCharacterOrigin |
P151
|
FINISHED |
| Object | Spanish |
—
|
LITERAL 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: Spanish | Statement: [Marquis de Casalduero, languageOfCharacterOrigin, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCharacterOrigin Context triple: [Marquis de Casalduero, languageOfCharacterOrigin, Spanish]
-
A.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
B.
languageOfFictionalUniverse
Indicates the language used or spoken within a fictional universe or setting.
-
C.
languageOfHonoredFigure
Indicates the language associated with or used by the person who is being honored.
-
D.
nativeLanguage
chosen
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
macrolanguageOf
Indicates that one language functions as a macrolanguage encompassing or grouping together one or more related individual languages.
- F. None of above.
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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:24 p.m.