Triple
T25279020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'd Do Anything for Love (But I Won't Do That) |
E633777
|
entity |
| Predicate | femaleVocalDuetWith |
P9649
|
FINISHED |
| Object | Lorraine Crosby |
—
|
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: Lorraine Crosby | Statement: [I'd Do Anything for Love (But I Won't Do That), femaleVocalDuetWith, Lorraine Crosby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femaleVocalDuetWith Context triple: [I'd Do Anything for Love (But I Won't Do That), femaleVocalDuetWith, Lorraine Crosby]
-
A.
hasVocalDuet
chosen
Indicates that two entities perform or participate together in a vocal duet.
-
B.
hasFemaleVocalist
Indicates that the subject entity features or includes at least one female vocalist as a performer.
-
C.
hasCallAndResponseVocals
Indicates that one entity produces vocalizations that are followed by corresponding or answering vocalizations from another entity.
-
D.
hasNotablePerformerDuo
Indicates that the subject has a notable performing duo associated with it, such as a well-known pair of artists or entertainers who perform together.
-
E.
vocalSoloists
Indicates that one or more entities perform as solo vocalists in a musical work or performance.
- 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_69e75a9402fc81909362ca85277c06d9 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48e01001c8190b57c66866ec9f626 |
completed | May 1, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 1:18 p.m.