Triple
T24532046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Cruz region |
E606835
|
entity |
| Predicate | regionalSpanishVariety |
P11942
|
FINISHED |
| Object | Camba Spanish |
—
|
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: Camba Spanish | Statement: [Santa Cruz region, regionalSpanishVariety, Camba Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalSpanishVariety Context triple: [Santa Cruz region, regionalSpanishVariety, Camba Spanish]
-
A.
regionalDialect
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
B.
SpanishObjective
Indicates that an entity is the target or goal of an action, relation, or expression specifically in the Spanish language.
-
C.
mainRegionInSpain
Indicates that a location is the primary or most significant region associated with a place or entity within Spain.
-
D.
regionalVariantOf
chosen
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
-
E.
partOfLinguisticVariety
Indicates that one linguistic variety (such as a dialect, register, or style) is a constituent or subset of another, broader linguistic variety.
- 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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:25 a.m.