Triple
T22484841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farmhouse |
E555851
|
entity |
| Predicate | hasSingle |
P3282
|
FINISHED |
| Object | Back on the Train |
—
|
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: Back on the Train | Statement: [Farmhouse, hasSingle, Back on the Train]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Back on the Train Context triple: [Farmhouse, hasSingle, Back on the Train]
-
A.
Back on the Train
chosen
"Back on the Train" is a song by the American rock band Phish, known for its groove-oriented, jam-friendly style and frequent live performances.
-
B.
Stop This Train
"Stop This Train" is a reflective folk-pop song by John Mayer that explores themes of aging, change, and the passage of time.
-
C.
This Train
"This Train" is a traditional American gospel song popularized by Sister Rosetta Tharpe, celebrated for its driving rhythm and moralistic lyrics about a righteous journey to salvation.
-
D.
This Train
"This Train" is a song by reggae artist International Herb, likely reflecting his roots-influenced style and themes.
-
E.
Stop the Train
"Stop the Train" is a song by American singer-songwriter Henry Wolfe, known for its mellow indie-pop style and introspective lyrics.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c3bb8cc8190950efd84ebe86b73 |
completed | April 29, 2026, 1:17 a.m. |
Created at: April 16, 2026, 8:49 p.m.