Triple

T10007564
Position Surface form Disambiguated ID Type / Status
Subject Little Voice E198290 entity
Predicate hasTrack P3284 FINISHED
Object Vegas E36474 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: Vegas | Statement: [Little Voice, hasTrack, Vegas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vegas
Context triple: [Little Voice, hasTrack, Vegas]
  • A. Bas Vegas
    Bas Vegas is a tongue-in-cheek nickname for the Essex town of Basildon, referencing its lively nightlife and entertainment venues in comparison to Las Vegas.
  • B. Las Vegas, Nevada chosen
    Las Vegas, Nevada is a major resort city in the Mojave Desert known for its vibrant nightlife, casinos, entertainment, and luxury hotels.
  • C. Santiago de las Vegas
    Santiago de las Vegas is a town in the municipality of Boyeros, Havana, Cuba, historically known as a suburban settlement of the capital.
  • D. Paris Las Vegas
    Paris Las Vegas is a French-themed hotel and casino on the Las Vegas Strip, known for its replica Eiffel Tower and Parisian-style architecture.
  • E. Reno
    Reno is a city in northwestern Nevada known for its casinos, tourism, and proximity to outdoor recreation areas in the Sierra Nevada, including Lake Tahoe.
  • 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_69ca830fcca48190bbbd9b20c233835f completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd187fe481908556ea896c528ea4 completed April 2, 2026, 1:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b5f15c6c8190b52924d6f86d63e0 completed April 5, 2026, 7:20 p.m.
Created at: March 30, 2026, 8:52 p.m.