Triple

T15355594
Position Surface form Disambiguated ID Type / Status
Subject Lego Ninjago E367163 entity
Predicate hasAntagonist P18963 FINISHED
Object Lord Garmadon E367215 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: Lord Garmadon | Statement: [Lego Ninjago, hasAntagonist, Lord Garmadon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lord Garmadon
Context triple: [Lego Ninjago, hasAntagonist, Lord Garmadon]
  • A. Lord Garmadon chosen
    Lord Garmadon is the four-armed, villainous warlord and estranged father of Lloyd who serves as the central antagonist in The Lego Ninjago Movie.
  • B. Lloyd Garmadon
    Lloyd Garmadon is the green ninja protagonist of the Lego Ninjago franchise, known for being the conflicted son of the evil warlord Garmadon.
  • C. Yen Sid
    Yen Sid is the powerful and enigmatic sorcerer from Disney's "Fantasia," best known as Mickey Mouse's stern magical mentor in "The Sorcerer's Apprentice" segment.
  • D. Kharis
    Kharis is a reanimated ancient Egyptian mummy who serves as the central monstrous antagonist in Universal Pictures’ classic Mummy film series.
  • E. Daken
    Daken is a fictional Marvel Comics antihero and mutant, best known as the son of Wolverine with retractable claws and a complex, morally ambiguous personality.
  • 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.