Triple

T12005480
Position Surface form Disambiguated ID Type / Status
Subject Goats Head Soup E285768 entity
Predicate hasPart P35 FINISHED
Object Silver Train E959406 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: Silver Train | Statement: [Goats Head Soup, hasPart, Silver Train]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silver Train
Context triple: [Goats Head Soup, hasPart, Silver Train]
  • A. Silver Train chosen
    "Silver Train" is a bluesy rock song by The Rolling Stones, released in 1973 and known for its gritty guitar riffs and train-themed lyrics.
  • B. Blue Train
    "Blue Train" is a song featured on the country album "Western Wall: The Tucson Sessions" by Linda Ronstadt and Emmylou Harris.
  • C. Blue Train
    "Blue Train" is a landmark 1957 hard bop jazz album by saxophonist John Coltrane, widely regarded as one of his greatest recordings and a classic of the Blue Note label.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c481a48190b311d6809808ef1b completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d259f7c81908366e7d9e61a6c73 completed May 1, 2026, 12:31 p.m.
Created at: April 8, 2026, 9:46 p.m.