Triple
T25279164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Objects in the Rear View Mirror May Appear Closer Than They Are |
E633780
|
entity |
| Predicate | sharesSongwriterWith |
P89585
|
FINISHED |
| Object | I Would Do Anything for Love (But I Won’t Do That) |
—
|
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: I Would Do Anything for Love (But I Won’t Do That) | Statement: [Objects in the Rear View Mirror May Appear Closer Than They Are, sharesSongwriterWith, I Would Do Anything for Love (But I Won’t Do That)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesSongwriterWith Context triple: [Objects in the Rear View Mirror May Appear Closer Than They Are, sharesSongwriterWith, I Would Do Anything for Love (But I Won’t Do That)]
-
A.
sharesSongwritersWith
chosen
Indicates that two musical works have at least one songwriter in common.
-
B.
sharesSong
Indicates that one entity provides or distributes a song to another entity.
-
C.
sharesComposerWith
Indicates that two musical works have been composed by the same composer.
-
D.
sharesMusicWith
Indicates that one entity provides or exchanges music with another entity.
-
E.
sharesMusiciansWith
Indicates that two musical groups or acts have one or more musicians in common.
- 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_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 21, 2026, 1:18 p.m.