Triple

T21143280
Position Surface form Disambiguated ID Type / Status
Subject The Amazing Spider-Man (comic series) E520985 entity
Predicate featuresCharacter P626 FINISHED
Object Kingpin 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: Kingpin | Statement: [The Amazing Spider-Man (comic series), featuresCharacter, Kingpin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kingpin
Context triple: [The Amazing Spider-Man (comic series), featuresCharacter, Kingpin]
  • A. Kingpin
    Kingpin is a 2003 television film that dramatizes the rise and fall of a powerful Mexican drug lord and his cartel.
  • B. Kingpin
    Kingpin is a 1996 sports comedy film about a washed-up former bowling prodigy who mentors an Amish bowling talent, known for its offbeat humor and cult following.
  • C. Kingpin chosen
    Kingpin is a powerful crime lord in the Marvel Universe, best known as a major adversary of heroes like Spider-Man and Daredevil.
  • D. Kingpin Suite
    Kingpin Suite is a luxury, bowling-themed hotel suite in Las Vegas known for its in-room bowling lanes and over-the-top entertainment amenities.
  • E. The Drug King
    The Drug King is a South Korean crime drama film that chronicles the rise and fall of a small-time smuggler who becomes a powerful drug lord in 1970s Busan.
  • 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_69e0b50c6a848190a4e525a77a319b8a completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e723fad02c8190a8e9fb82f0491642 completed April 21, 2026, 7:15 a.m.
Created at: April 16, 2026, 2:57 p.m.