Triple
T31049399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Round Every Corner |
E791215
|
entity |
| Predicate | followsMusicalTrendOf |
P139778
|
FINISHED |
| Object | mid-1960s Petula Clark hits |
—
|
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: mid-1960s Petula Clark hits | Statement: [Round Every Corner, followsMusicalTrendOf, mid-1960s Petula Clark hits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsMusicalTrendOf Context triple: [Round Every Corner, followsMusicalTrendOf, mid-1960s Petula Clark hits]
-
A.
hasMusicalStyleSimilarTo
Indicates that two entities share a comparable or closely related musical style or sound.
-
B.
followsSoundOf
Indicates that one entity moves or directs its attention by tracking the source or direction of a sound produced by another entity.
-
C.
oftenTunesTo
Indicates that one entity frequently adjusts or sets its frequency, settings, or focus to match or receive another entity.
-
D.
musicStyleShiftToward
chosen
Indicates a change in musical style or genre moving in the direction of another specified style.
-
E.
genreTrend
Indicates how the popularity or prevalence of a particular genre changes over time or across contexts.
- 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_69f224cb08908190ba71ad9aa87518ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 29, 2026, 9 p.m.