Triple
T30547409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baby, Can You Dig Your Man? |
E777457
|
entity |
| Predicate | usedAsMotif |
P41002
|
FINISHED |
| Object | theme of fame and responsibility |
—
|
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: theme of fame and responsibility | Statement: [Baby, Can You Dig Your Man?, usedAsMotif, theme of fame and responsibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsMotif Context triple: [Baby, Can You Dig Your Man?, usedAsMotif, theme of fame and responsibility]
-
A.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from another entity.
-
B.
featuresMotif
chosen
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
-
C.
transformationMotif
Indicates a recurring pattern or theme in which one entity undergoes a change in form, state, or identity in relation to another.
-
D.
commonMotifRegion
Indicates that two or more entities share a recurring motif within the same spatial or contextual region.
-
E.
reverseMotif
Indicates that one motif is the reversed or inverted form of another motif in structure, order, or direction.
- 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_69f2249e19108190a458ab446096bf22 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: April 29, 2026, 8:19 p.m.