Triple
T20487993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ridin’ High |
E502654
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Red, Hot and Blue |
—
|
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: Red, Hot and Blue | Statement: [Ridin’ High, partOf, Red, Hot and Blue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Red, Hot and Blue Context triple: [Ridin’ High, partOf, Red, Hot and Blue]
-
A.
Red, Hot and Blue
chosen
Red, Hot and Blue is a 1936 Broadway musical comedy with music and lyrics by Cole Porter, known for its witty songs and star-studded original cast.
-
B.
Red Hot
"Red Hot" is a 1993 drama film set in Soviet-era Latvia, following a group of young musicians who risk severe punishment to secretly play Western rock music.
-
C.
Dazzling Blue
"Dazzling Blue" is a reflective, folk-infused song by Paul Simon that blends intricate acoustic guitar work with poetic lyrics on love and spirituality.
-
D.
Sugar Blue
Sugar Blue is an American blues harmonica virtuoso known for his innovative, high-intensity playing style and work with artists such as the Rolling Stones.
-
E.
Burning Blue
Burning Blue is a 2013 drama film about U.S. Navy fighter pilots whose careers and relationships are tested when a forbidden romance and a series of accidents spark a military investigation.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b5c6f84819087d813be3542ed33 |
completed | April 20, 2026, 9:32 p.m. |
Created at: April 16, 2026, 11:34 a.m.