Triple
T31289166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erotic City |
E797886
|
entity |
| Predicate | hasBsideOrAasBsideOf |
P15273
|
FINISHED |
| Object | Let’s Go Crazy |
—
|
NE NERFINISHED |
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: Let’s Go Crazy | Statement: [Erotic City, hasBsideOrAasBsideOf, Let’s Go Crazy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBsideOrAasBsideOf Context triple: [Erotic City, hasBsideOrAasBsideOf, Let’s Go Crazy]
-
A.
hasBside
chosen
Indicates that one item serves as the B-side counterpart or secondary track associated with another primary item, typically in a recording or media release.
-
B.
hasBsideStatus
Indicates that one item (typically a song or track) holds the status of being the B-side counterpart to another primary item (such as an A-side single).
-
C.
isBSideOf
Indicates that one entity is located on the B side or secondary face of another entity, typically in a two-sided or dual-orientation context.
-
D.
hasASideOf
Indicates that one entity possesses or includes a particular side or face as part of its structure or boundary.
-
E.
isOnSideAOrB
Indicates that an entity is located on either side A or side B of a specified reference or boundary.
- 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:14 p.m.