Triple
T20520194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Should I Stay or Should I Go |
E503786
|
entity |
| Predicate | featuresBilingualVocals |
P105279
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Should I Stay or Should I Go, featuresBilingualVocals, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresBilingualVocals Context triple: [Should I Stay or Should I Go, featuresBilingualVocals, true]
-
A.
hasVocalLanguageMix
chosen
Indicates that an entity’s vocal communication combines multiple languages or language varieties within its speech.
-
B.
hasVocalDuet
Indicates that two entities perform or participate together in a vocal duet.
-
C.
hasVocals
Indicates that the subject includes or features vocal elements, such as singing or spoken voice, rather than being purely instrumental or non-vocal.
-
D.
usesMultiTrackVocals
Indicates that the subject employs multiple separately recorded vocal tracks layered together in the audio or performance.
-
E.
hasBackwardVocals
Indicates that the subject uses or contains backward (reversed) vocal audio in relation to the object.
- 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f4587c481908544f89572d164b0 |
completed | April 20, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:36 a.m.