Triple
T20107789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cafe Racers |
E490234
|
entity |
| Predicate | performs |
P2297
|
FINISHED |
| Object | The Universal Song |
—
|
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: The Universal Song | Statement: [Cafe Racers, performs, The Universal Song]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Universal Song Context triple: [Cafe Racers, performs, The Universal Song]
-
A.
The Universal Song
chosen
The Universal Song is a track by the band Cafe Racers, likely reflecting their signature style within their musical catalog.
-
B.
Our Song
"Our Song" is a breakout country single by Taylor Swift that she wrote in high school, known for its catchy storytelling about young love and everyday moments.
-
C.
Our Song
"Our Song" is a track by the English progressive rock band Yes, featured on their 1983 album "90125."
-
D.
The Good Old Song
The Good Old Song is the traditional alma mater-style anthem of the University of Virginia, famously sung by fans and students at Virginia Cavaliers sporting events.
-
E.
A Song
"A Song" is a track by Greek composer Vangelis featured on his 1979 electronic music album "Earth."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666ddb09881909ad2aedd1e8a78da |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:28 p.m.