Triple

T15356136
Position Surface form Disambiguated ID Type / Status
Subject AFOL E367171 entity
Predicate hasTheme P261 FINISHED
Object Lego City E367161 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: Lego City | Statement: [AFOL, hasTheme, Lego City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lego City
Context triple: [AFOL, hasTheme, 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 Pirates
    Lego Pirates is a classic Lego theme centered on swashbuckling pirate adventures, featuring ships, forts, treasure islands, and minifigure crews.
  • E. Block City
    Block City is a compact, block-themed battle arena course featured in the multiplayer Battle Mode of Mario Kart: Double Dash!!.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e2c00648190ae2325e1ee58dcfd completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff364d82c48190b116528b5c00e918 completed May 9, 2026, 1:27 p.m.
Created at: April 10, 2026, 3:18 a.m.