Triple
T5854381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oscar Peterson |
E130113
|
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, notableWork, Night Train]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Night Train Context triple: [Oscar Peterson, 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.
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.
-
D.
Ghost Train
Ghost Train is a classic dark ride attraction featuring spooky scenes and special effects, located at the Blackpool Pleasure Beach amusement park in England.
-
E.
Light Train
Light Train is a type of urban rail transit system characterized by relatively low weight vehicles, moderate capacity, and operation often on dedicated or semi-exclusive tracks for short- to medium-distance passenger transport.
- 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_69c0084de39081909eb34e6bed74215a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03554651c8190b3009d41eecf6779 |
completed | March 22, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1bc58d081908568294278cbf3a9 |
completed | March 23, 2026, 2:13 a.m. |
Created at: March 22, 2026, 3:55 p.m.