Triple
T23260711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Think I Love Her |
E581996
|
entity |
| Predicate | usesBeat |
P151235
|
FINISHED |
| Object | borrowed beat |
—
|
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: borrowed beat | Statement: [I Think I Love Her, usesBeat, borrowed beat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBeat Context triple: [I Think I Love Her, usesBeat, borrowed beat]
-
A.
usesBeatFrom
chosen
Indicates that one entity employs or incorporates the rhythmic pattern, instrumental backing, or beat originally created for or associated with another entity.
-
B.
hasBeat
Indicates that one entity has defeated or surpassed another in a competitive or comparative context.
-
C.
originalBeatBy
Indicates that one entity was initially defeated, surpassed, or outperformed by another entity.
-
D.
hasNotableBeat
Indicates that an entity (such as a journalist or reporter) is professionally assigned to cover a specific topic, area, or subject as their primary reporting focus.
-
E.
hasDrivingBeat
Indicates that something (typically a piece of music) features a strong, steady, and rhythmically propulsive beat that drives its momentum.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c9189c8190a13c17c635227f42 |
completed | April 29, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:11 p.m.