Triple

T4924708
Position Surface form Disambiguated ID Type / Status
Subject Mr. Hockey E110548 entity
Predicate playedWithSonOnSameTeam P21799 FINISHED
Object Mark Howe E56176 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: Mark Howe | Statement: [Mr. Hockey, playedWithSonOnSameTeam, Mark Howe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Howe
Context triple: [Mr. Hockey, playedWithSonOnSameTeam, Mark Howe]
  • A. Mark Howe chosen
    Mark Howe is a Hall of Fame American defenseman renowned for his stellar two-way play and leadership with the Philadelphia Flyers in the 1980s.
  • B. Jim Norris
    Jim Norris is a technology entrepreneur best known as one of the founders of the innovative microprocessor company Transmeta.
  • C. Phil Esposito
    Phil Esposito is a Hall of Fame Canadian center renowned as one of the NHL’s greatest goal scorers and a key offensive star of the late 1960s and 1970s.
  • D. Bill Guerin
    Bill Guerin is a former NHL forward and two-time Stanley Cup champion who now serves as an executive in professional ice hockey.
  • E. Joe Nieuwendyk
    Joe Nieuwendyk is a Canadian former professional ice hockey center and Hockey Hall of Famer known for winning multiple Stanley Cups and the Calder Memorial Trophy during his NHL career.
  • 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_69bd4413f9908190afcff44d7929cc4c completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ffeb86c8190a2fabe1ae1d54118 completed March 20, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89e731a4819087bf2e55215654d9 completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:30 p.m.