Triple

T20967058
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Lounge E516393 entity
Predicate locatedInCity P40 FINISHED
Object Lake Buena Vista 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: Lake Buena Vista | Statement: [Barcelona Lounge, locatedInCity, Lake Buena Vista]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Buena Vista
Context triple: [Barcelona Lounge, locatedInCity, Lake Buena Vista]
  • A. Lake Buena Vista, Florida chosen
    Lake Buena Vista, Florida is a small city in Orange County best known as the municipal home of the Walt Disney World Resort and other Disney-related properties.
  • B. Lake Mary
    Lake Mary is a scenic alpine lake near Mammoth Lakes in California, popular for fishing, boating, and outdoor recreation amid mountain and forest surroundings.
  • C. Lake Mary
    Lake Mary is a popular reservoir in northern Arizona known for fishing, boating, and scenic forested surroundings near Flagstaff.
  • D. Windermere, Florida
    Windermere, Florida is a small, affluent town in Orange County known for its lakeside residential communities and proximity to Orlando.
  • E. Lake Mary, Florida
    Lake Mary, Florida is a suburban city in Seminole County known for its affluent residential communities, strong public schools, and concentration of high-tech and corporate offices within the greater Orlando area.
  • 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_69e0b4fde6c48190af1398e7e734629e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fb74206c819099f9c67eaca45ec1 completed April 21, 2026, 4:22 a.m.
Created at: April 16, 2026, 1:33 p.m.