Triple
T61496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerto Rican Spanish |
E1221
|
entity |
| Predicate | hasRegionalVariation |
P455
|
FINISHED |
| Object | urban speech varieties |
—
|
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: urban speech varieties | Statement: [Puerto Rican Spanish, hasRegionalVariation, urban speech varieties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalVariation Context triple: [Puerto Rican Spanish, hasRegionalVariation, urban speech varieties]
-
A.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
-
B.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
-
C.
regionalDialect
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
D.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
E.
hasVariant
chosen
Indicates that one entity exists as an alternative form, version, or variation of another entity.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251f74b0881909ad89127b8171277 |
completed | Feb. 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69a24ea242c8819086fe00bf01e6523e |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.