Triple
T9326345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cheek to Cheek ballroom dance |
E224394
|
entity |
| Predicate | musicTempo |
P83539
|
FINISHED |
| Object | slow foxtrot tempo |
—
|
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: slow foxtrot tempo | Statement: [Cheek to Cheek ballroom dance, musicTempo, slow foxtrot tempo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musicTempo Context triple: [Cheek to Cheek ballroom dance, musicTempo, slow foxtrot tempo]
-
A.
hasTempoChanges
Indicates that the tempo of the piece or segment changes over its duration, rather than remaining constant.
-
B.
typicalTempoControl
Indicates that one entity serves as the usual or standard means by which the tempo of another entity (such as a process or activity) is regulated or controlled.
-
C.
hasTempoCategory
chosen
Indicates that something is associated with a particular tempo classification or speed category.
-
D.
featuresMoreUpTempoTracksThan
Indicates that one entity has a greater number of up-tempo tracks than another entity.
-
E.
hasBPMApprox
Indicates an approximate beats-per-minute (BPM) value associated with an entity, rather than an exact measured tempo.
- 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_69ca8427a0c08190b749831d5ea98f02 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd36f88e988190bb896a3d7c3c723c |
completed | April 1, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69cc7a643924819097f01144734901cf |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:39 p.m.