Triple

T23038732
Position Surface form Disambiguated ID Type / Status
Subject Legoland Florida E573677 entity
Predicate hasSection P35 FINISHED
Object Lego City 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: Lego City | Statement: [Legoland Florida, hasSection, Lego City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lego City
Context triple: [Legoland Florida, hasSection, Lego City]
  • A. Lego City chosen
    Lego City is a popular Lego theme that depicts everyday urban life with sets featuring vehicles, buildings, emergency services, and city infrastructure.
  • B. Lego City Undercover
    Lego City Undercover is an action-adventure video game set in an open-world LEGO city where players control undercover cop Chase McCain on a comedic crime-fighting adventure.
  • C. Lego House
    Lego House is an experience center and museum in Billund, Denmark, designed to resemble a giant stack of LEGO bricks and celebrate the history and creativity of the LEGO brand.
  • D. LEGO Worlds
    LEGO Worlds is a sandbox video game that lets players build, explore, and customize procedurally generated LEGO environments using virtual bricks.
  • E. Lego Pirates
    Lego Pirates is a classic Lego theme centered on swashbuckling pirate adventures, featuring ships, forts, treasure islands, and minifigure crews.
  • 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_69e245b911188190bc3d96326c847969 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f185121da0819095b523d7d2c923ab completed April 29, 2026, 4:12 a.m.
Created at: April 17, 2026, 3:53 p.m.