Triple

T21252235
Position Surface form Disambiguated ID Type / Status
Subject Spider-Army E523772 entity
Predicate hasMember P10 FINISHED
Object Spider-Gwen 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: Spider-Gwen | Statement: [Spider-Army, hasMember, Spider-Gwen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spider-Gwen
Context triple: [Spider-Army, hasMember, Spider-Gwen]
  • A. Spider-Gwen chosen
    Spider-Gwen is an alternate-universe version of Gwen Stacy who becomes a spider-powered superhero and a prominent member of Marvel’s Spider-Verse.
  • B. Spider-Girl
    Spider-Girl is a Marvel Comics superheroine, often depicted as a teenage successor to Spider-Man who inherits his powers and mantle in alternate future timelines.
  • C. Spider-Man Noir
    Spider-Man Noir is a gritty, alternate-universe version of Spider-Man from a 1930s-inspired, black-and-white world, known for his trench coat, fedora, and hard-boiled detective style.
  • D. Madame Web
    Madame Web is a 2024 superhero film in Sony's Spider-Man Universe that follows a clairvoyant paramedic who gains psychic abilities and becomes entangled in a web of destiny.
  • E. Spider-Woman
    Spider-Woman is a Marvel Comics superheroine, most commonly Jessica Drew, known for her spider-based powers, espionage background, and membership in major superhero teams.
  • 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_69e0b5146c108190adc9adb73e90abff completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7359f5b408190b951adddba83c97a completed April 21, 2026, 8:30 a.m.
Created at: April 16, 2026, 3:57 p.m.