Triple
T220565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taíno |
E4202
|
entity |
| Predicate | loanwordInSpanish |
P5695
|
FINISHED |
| Object | huracán |
—
|
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: huracán | Statement: [Taíno, loanwordInSpanish, huracán]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loanwordInSpanish Context triple: [Taíno, loanwordInSpanish, huracán]
-
A.
fractionalNameInSpanish
Indicates that an entity’s fractional value is expressed or named in the Spanish language.
-
B.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
-
C.
hasSignificantSpanishInfluence
Indicates that one entity has been strongly shaped or notably affected by Spanish culture, language, practices, or presence.
-
D.
officialNameInSpanish
Indicates the officially recognized name of an entity when expressed in the Spanish language.
-
E.
lexicalItem
chosen
Indicates that one entity is a word or vocabulary unit associated with, or used to express, another entity (such as a concept, meaning, or linguistic entry).
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25efd0df48190b8fef4c422a1265f |
completed | Feb. 28, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69a25b54d790819093b35bd1a6f00f92 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.