Triple

T9280605
Position Surface form Disambiguated ID Type / Status
Subject Al Franken (guest host) E223055 entity
Predicate represented P192 FINISHED
Object Minnesota E33799 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: Minnesota | Statement: [Al Franken (guest host), represented, Minnesota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Minnesota
Context triple: [Al Franken (guest host), represented, Minnesota]
  • A. Minnesota chosen
    Minnesota is a U.S. state known for its numerous lakes, cold winters, and vibrant cultural and economic centers like Minneapolis–Saint Paul.
  • B. Minnesota
    Minnesota is an American hip hop record producer known for his work with prominent rap artists in the 1990s and 2000s.
  • C. Minnesota
    Minnesota is an American electronic music producer and DJ known for his melodic, bass-heavy dubstep and festival performances.
  • D. D. Minn.
    D. Minn. is the standard legal abbreviation for the United States District Court for the District of Minnesota, a federal trial court within the Eighth Circuit.
  • E. Minnesota and Wisconsin
    Minnesota and Wisconsin are two neighboring U.S. states in the Upper Midwest, known for their abundant lakes, forests, and shared border along the upper Mississippi River.
  • 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_69ca842123588190b3f2e1a69037d141 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd07cd9a1c8190af0521baa428ce10 completed April 1, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0f38f99b88190bb979bf9255c07d7 completed April 4, 2026, 11:18 a.m.
Created at: March 30, 2026, 7:34 p.m.