Triple

T13594731
Position Surface form Disambiguated ID Type / Status
Subject Lt. Mike Stone E324786 entity
Predicate fullName P16 FINISHED
Object Michael Stone E252879 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: Michael Stone | Statement: [Lt. Mike Stone, fullName, Michael Stone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Stone
Context triple: [Lt. Mike Stone, fullName, Michael Stone]
  • A. Michael Stone chosen
    Michael Stone is a common name shared by several notable individuals, including professionals in fields such as politics, sports, academia, and the arts.
  • B. Fred Stone
    Fred Stone was an American stage and film actor, dancer, and vaudevillian best known for his comedic roles in early 20th-century Broadway productions.
  • C. Christopher Isaac Stone
    Christopher Isaac Stone, better known as Biz Stone, is an American entrepreneur and software developer best known as a co-founder of Twitter.
  • D. Christopher Stone
    Christopher Stone was an American actor known for his work in film and television, including frequent collaborations with his wife, actress Dee Wallace.
  • E. David Stone
    David Stone is a screenwriter known for his work on the psychological horror film "Repulsion," contributing to its tense, character-driven narrative.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb057f1c881909a3bb77c659a724a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bc762a08190b5d29cef9923da84 completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:49 p.m.