Triple
T8424599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sampling Corona’s 1993 hit The Rhythm of the Night |
E198945
|
entity |
| Predicate | languageOfTarget |
P56541
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [sampling Corona’s 1993 hit The Rhythm of the Night, languageOfTarget, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfTarget Context triple: [sampling Corona’s 1993 hit The Rhythm of the Night, languageOfTarget, English]
-
A.
targetLanguage
chosen
Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
-
B.
translationTargetLanguage
Indicates the language into which content is being or has been translated.
-
C.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
D.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
E.
languageOfInterpretation
Indicates the language in which something (such as text, speech, or content) is interpreted or understood.
- 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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb85a0d04481908a5da908cafeceaa |
completed | March 31, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:07 p.m.