Triple

T21350309
Position Surface form Disambiguated ID Type / Status
Subject Tina Goldstein E526456 entity
Predicate loyalty P1201 FINISHED
Object MACUSA 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: MACUSA | Statement: [Tina Goldstein, loyalty, MACUSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MACUSA
Context triple: [Tina Goldstein, loyalty, MACUSA]
  • A. MACUSA chosen
    MACUSA is the Magical Congress of the United States of America, the governing body for witches and wizards in the U.S. in the Wizarding World.
  • B. US-DC
    US-DC is the ISO 3166-2 code representing the District of Columbia, the federal district containing the capital city of the United States, Washington, D.C.
  • C. Amerks
    Amerks is the common nickname for the Rochester Americans, a professional ice hockey team in the American Hockey League.
  • D. U.S.S.A.
    U.S.S.A. is an experimental rock band featuring guitarist Duane Denison that blends elements of alternative, industrial, and avant-garde music.
  • E. Genosha
    Genosha is a fictional island nation in Marvel Comics, notorious for its history of mutant enslavement, political upheaval, and catastrophic destruction.
  • 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8ad31087481909d41e9d28286f04d completed April 22, 2026, 11:12 a.m.
Created at: April 16, 2026, 5:03 p.m.