Triple
T31435176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Entremeses Cervantinos |
E801904
|
entity |
| Predicate | usedLanguageRegister |
P109329
|
FINISHED |
| Object | colloquial 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: colloquial Spanish | Statement: [Entremeses Cervantinos, usedLanguageRegister, colloquial Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLanguageRegister Context triple: [Entremeses Cervantinos, usedLanguageRegister, colloquial Spanish]
-
A.
usesLanguageRegister
chosen
Indicates that an entity communicates using a particular language register or style (e.g., formal, informal, technical) in a given context.
-
B.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
C.
usesLanguageAs
Indicates that one entity communicates or operates using another entity as its language or linguistic medium.
-
D.
adoptedLanguage
Indicates that an entity has chosen and begun using a particular language, typically as its official, primary, or preferred means of communication.
-
E.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
- 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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 9:01 p.m.