Triple

T970386
Position Surface form Disambiguated ID Type / Status
Subject Max E20930 entity
Predicate hasContentFrom P22683 FINISHED
Object DC Entertainment E18704 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: DC Entertainment | Statement: [Max, hasContentFrom, DC Entertainment]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DC Entertainment
Context triple: [Max, hasContentFrom, DC Entertainment]
  • A. DC Comics chosen
    DC Comics is a major American comic book publisher best known for iconic superhero characters such as Superman, Batman, and Wonder Woman.
  • B. Marvel Comics
    Marvel Comics is a major American comic book publisher best known for creating the Marvel Universe, home to iconic superheroes such as Spider-Man, Iron Man, the X-Men, and Captain America.
  • C. DC Universe
    The DC Universe is a fictional superhero setting featuring characters like Superman, Batman, and Wonder Woman who coexist and interact across interconnected stories and worlds.
  • D. DCU
    DCU is the common abbreviation for D.C. United, a professional Major League Soccer club based in Washington, D.C.
  • E. DC Extended Universe
    The DC Extended Universe is a shared cinematic universe of superhero films and related media based on DC Comics characters, featuring interconnected stories and recurring characters across multiple movies.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b75103688190a14342eef3842984 completed March 1, 2026, 10:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2586fd7c8190ba77b327bad4bb69 completed March 7, 2026, 1:17 p.m.
Created at: March 1, 2026, 7:40 p.m.