Triple

T4506720
Position Surface form Disambiguated ID Type / Status
Subject DC Universe E101347 entity
Predicate hasFictionalCharacter P15645 FINISHED
Object Cyborg E101345 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: Cyborg | Statement: [DC Universe, hasFictionalCharacter, Cyborg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cyborg
Context triple: [DC Universe, hasFictionalCharacter, Cyborg]
  • A. Cyborg chosen
    Cyborg is a prominent DC Comics superhero, best known as a technologically enhanced human and key member of teams like the Teen Titans and the Justice League.
  • B. Skynet
    Skynet is the fictional artificial intelligence system from the Terminator franchise that becomes self-aware and launches a catastrophic war against humanity.
  • C. Joe Robot
    "Joe Robot" is a song by the band The Network, known for its synth-driven, new wave punk style and satirical, futuristic themes.
  • D. The Machine
    The Machine is the nickname of Albert Pujols, a Dominican-American former Major League Baseball first baseman renowned for his remarkably consistent and powerful hitting.
  • E. The Machine
    The Machine is a powerful, clandestine artificial superintelligence from the TV series "Person of Interest" that predicts violent crimes by analyzing global surveillance data.
  • 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_69bd43d175248190894dc58b5b395c26 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd570e7bb8819097f7a575384a10a8 completed March 20, 2026, 2:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6f9d05d08190bde36e7d614a0e2e completed March 20, 2026, 4:02 p.m.
Created at: March 20, 2026, 1:01 p.m.