Triple
T10145281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacobo |
E231687
|
entity |
| Predicate | notableLanguageContext |
P8383
|
FINISHED |
| Object | Spanish-speaking cultures |
—
|
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-speaking cultures | Statement: [Jacobo, notableLanguageContext, Spanish-speaking cultures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageContext Context triple: [Jacobo, notableLanguageContext, Spanish-speaking cultures]
-
A.
hasLanguageContext
chosen
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
notableMemberLanguage
Indicates that the language is notably associated with or used by a prominent member of the referenced group or entity.
-
C.
notableDialect
Indicates that an entity is recognized for having a distinct or noteworthy dialect associated with it.
-
D.
notableRuleContext
Indicates that a rule, regulation, or guideline is being applied or interpreted within a particularly important or noteworthy contextual situation.
-
E.
hasLanguageUsageNote
Indicates that there is an associated note describing specific usage guidance, nuances, or restrictions for a language element.
- 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_69ca848364f881908a24366a6feec1db |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdeb2a373081908615f7b2314e7f90 |
completed | April 2, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba4f5d88190ba68e63be10b08c7 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:07 p.m.