Triple

T20349184
Position Surface form Disambiguated ID Type / Status
Subject Dragon Challenge E495962 entity
Predicate virtualQueueName P119996 FINISHED
Object Universal Express 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: Universal Express | Statement: [Dragon Challenge, virtualQueueName, Universal Express]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Universal Express
Context triple: [Dragon Challenge, virtualQueueName, Universal Express]
  • A. Universal Express chosen
    Universal Express is a paid line-skipping system used at Universal theme parks to reduce wait times for popular attractions.
  • B. UP Express
    UP Express is a dedicated airport rail link in Toronto that provides fast, frequent train service between Union Station downtown and Toronto Pearson International Airport.
  • C. Xpress
    Xpress is a regional public transit service in Georgia that provides commuter bus connections between suburban areas and major employment centers.
  • D. Green Express
    Green Express is a regional bus route operated by SolanoExpress that provides public transit service within the Solano County area and connections to neighboring communities.
  • E. International Express
    International Express is a nickname for New York City's 7 subway line, known for serving diverse immigrant neighborhoods across Queens and connecting them to Manhattan.
  • 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_69e0b4a3320881909495ae8bc30bc2dc completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6783af5dc8190a40c3b9816cd1aef completed April 20, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:24 a.m.