Triple
T11028624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moving Too Fast |
E260697
|
entity |
| Predicate | popularUse |
P68012
|
FINISHED |
| Object | audition song for male musical theatre performers |
—
|
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: audition song for male musical theatre performers | Statement: [Moving Too Fast, popularUse, audition song for male musical theatre performers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularUse Context triple: [Moving Too Fast, popularUse, audition song for male musical theatre performers]
-
A.
usageAmong
chosen
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
B.
popularDescription
Indicates that an entity has a commonly used or widely recognized descriptive text or label associated with it.
-
C.
popularFor
Indicates that something is widely liked, recognized, or favored specifically because of a particular feature, quality, or use.
-
D.
popularFrom
Indicates that something gains or holds popularity starting from a specific time, source, or context.
-
E.
commonUseCategory
Indicates that multiple entities share the same general category of use or functional purpose.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d245a0819085135cdee9b256c5 |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d7440087ac8190aef2e6f6b13b2635 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:25 p.m.