Triple

T2786049
Position Surface form Disambiguated ID Type / Status
Subject Judge Dredd E61812 entity
Predicate cityOfResidence P24950 FINISHED
Object Mega-City One E300158 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: Mega-City One | Statement: [Judge Dredd, cityOfResidence, Mega-City One]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mega-City One
Context triple: [Judge Dredd, cityOfResidence, Mega-City One]
  • A. Mega-City One chosen
    Mega-City One is a vast, dystopian future megapolis in the Judge Dredd universe, characterized by extreme overpopulation, crime, and authoritarian rule by the Judges.
  • B. Maximum City
    Maximum City is a popular nickname for Mumbai that reflects its vast scale, intense energy, and extreme contrasts in wealth, culture, and daily life.
  • C. Bogo City
    Bogo City is a component city in the northern part of Cebu province in the Philippines, known as a commercial and transport hub for surrounding rural municipalities.
  • D. Star City
    Star City is a commonly used nickname for the city of Lincoln, Nebraska.
  • E. Albertopolis
    Albertopolis is the South Kensington cultural and educational district in London, developed in the Victorian era around institutions like museums and colleges inspired by Prince Albert’s vision for arts and science.
  • 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_69ab4b7f51d881908768300ebd2fbdae completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abddb0d3488190a3f2bf47ebb35802 completed March 7, 2026, 8:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce8c2a088190824c1a720db05382 completed March 10, 2026, 7:55 a.m.
Created at: March 6, 2026, 9:57 p.m.