Triple

T15355936
Position Surface form Disambiguated ID Type / Status
Subject Lego DC Super Heroes E367168 entity
Predicate featuresLocation P7690 FINISHED
Object Metropolis E199719 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: Metropolis | Statement: [Lego DC Super Heroes, featuresLocation, Metropolis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metropolis
Context triple: [Lego DC Super Heroes, featuresLocation, Metropolis]
  • A. Metropolis
    Metropolis is a major Ethereum protocol upgrade that introduced significant improvements to scalability, security, and usability of the blockchain.
  • B. Metropolis
    Metropolis is a family of modern, high-capacity metro trains developed by Alstom for urban rapid transit systems worldwide.
  • C. Metropolis
    Metropolis is a science fiction television series inspired by Fritz Lang’s classic 1927 film, exploring a futuristic city divided by class and technological power.
  • D. Metropolis
    Metropolis is a major urban area of London that historically fell under the jurisdiction of Peel’s Act, which established the modern professional police force.
  • E. Metropolis chosen
    Metropolis is a fictional, futuristic American city in the DC Comics universe, best known as Superman’s primary home and the backdrop for many of his stories.
  • 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_69ff02012fa48190a108f1ca710ffb15 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:18 a.m.