Triple

T5742922
Position Surface form Disambiguated ID Type / Status
Subject Michael Green E126657 entity
Predicate wrote P2831 FINISHED
Object Green Lantern E101339 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: Green Lantern | Statement: [Michael Green, wrote, Green Lantern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Lantern
Context triple: [Michael Green, wrote, Green Lantern]
  • A. Green Lantern chosen
    Green Lantern is a long-running DC Comics superhero franchise centered on intergalactic peacekeepers who wield power rings fueled by willpower.
  • B. Green Lantern
    Green Lantern is a stand-up steel roller coaster at Six Flags Great Adventure themed after the DC Comics superhero.
  • C. Mister Miracle
    Mister Miracle is a DC Comics superhero and master escape artist created by Jack Kirby as part of his Fourth World saga.
  • D. Guardian of the Universe
    Guardian of the Universe is an epithet for Gamera, the giant flying turtle kaiju from Japanese films who protects humanity from monstrous threats.
  • E. The Peacemaker
    The Peacemaker is the legendary spiritual leader credited with uniting the Haudenosaunee (Iroquois) nations under the Great Law of Peace.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c025852a2c819080521e5b98c00bdc completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097f9b6e08190bb68ea850ba813ff completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:48 p.m.