Triple
T20453219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blush |
E501707
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | So Long |
—
|
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: So Long | Statement: [Blush, hasPart, So Long]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: So Long Context triple: [Blush, hasPart, So Long]
-
A.
So Long
chosen
"So Long" is a song by Swedish pop group ABBA, released in 1974 as a high-energy rock-influenced single.
-
B.
So Long Self
"So Long Self" is a contemporary Christian pop-rock song by MercyMe that reflects on letting go of selfishness and embracing a Christ-centered life.
-
C.
So Long Baby
"So Long Baby" is a rock and roll song by Del Shannon, featured as a track on his album "Runaway with Del Shannon."
-
D.
So Long, Farewell
"So Long, Farewell" is a popular song from the 1959 Rodgers and Hammerstein musical *The Sound of Music*, known for its playful farewell sequence performed by the von Trapp children.
-
E.
Gone So Long
"Gone So Long" is a novel by Andre Dubus III that explores the long-term emotional fallout of a violent crime through the fraught reunion of an estranged father and daughter.
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68d039af08190827bf765b50515a8 |
completed | April 20, 2026, 8:30 p.m. |
Created at: April 16, 2026, 11:32 a.m.