Triple

T8515818
Position Surface form Disambiguated ID Type / Status
Subject Zack Snyder's Justice League E201567 entity
Predicate featuresCharacter P626 FINISHED
Object Mera E203763 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: Mera | Statement: [Zack Snyder's Justice League, featuresCharacter, Mera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mera
Context triple: [Zack Snyder's Justice League, featuresCharacter, Mera]
  • A. Mera chosen
    Mera is a powerful Atlantean warrior and sorceress from DC Comics, best known as Aquaman’s ally and queen of Atlantis.
  • B. Mekhu
    Mekhu was an ancient Egyptian official and noble whose rock-cut tomb is located among the Tombs of the Nobles at Aswan.
  • C. Uma
    Uma is a central antagonist in Disney's "Descendants" franchise, known as the ambitious and strong-willed daughter of Ursula who leads a pirate crew on the Isle of the Lost.
  • D. Uma
    Uma is an Austronesian language spoken primarily in Central Sulawesi, Indonesia.
  • E. Uma
    Uma is a Bengali film directed by Srijit Mukherji, inspired by a real-life story of a terminally ill girl whose father recreates the Durga Puja festival early so she can experience it.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60f37b0819082ae14e539f57b56 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e5dbb3c81909157e6b04a4956af completed April 2, 2026, 11:09 a.m.
Created at: March 30, 2026, 6:15 p.m.