Triple
T15958207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oscar Peterson Trio |
E386989
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Night Train |
E387142
|
NE FINISHED |
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: Night Train | Statement: [Oscar Peterson Trio, notableWork, Night Train]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Night Train Context triple: [Oscar Peterson Trio, notableWork, Night Train]
-
A.
Night Train
chosen
Night Train is a celebrated jazz album featuring bassist Ray Brown, known for its swinging, blues-inflected interpretations of standards.
-
B.
Night Train
"Night Train" is a song by the English alternative rock band Keane, known for its melodic style and emotive lyrics.
-
C.
Night Train
Night Train is a Harley-Davidson Softail motorcycle model known for its stripped-down, blacked-out styling and custom cruiser appearance.
-
D.
Night Train
"Night Train" is a 1997 noir-influenced crime novel by British author Martin Amis that subverts the traditional detective story through a darkly comic, philosophical exploration of suicide and meaning.
-
E.
Sleep Train
Sleep Train is a former American mattress retail chain known for its extensive network of bedding stores, particularly in the western United States.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156fd7ce08190b5db4b486ccb6e40 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe7e76d481909e6f1d1ea33edd60 |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:53 a.m.