Triple

T15437304
Position Surface form Disambiguated ID Type / Status
Subject Allie Jones E369797 entity
Predicate createdBy P806 FINISHED
Object John Lutz E982778 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: John Lutz | Statement: [Allie Jones, createdBy, John Lutz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Lutz
Context triple: [Allie Jones, createdBy, John Lutz]
  • A. John Lutz chosen
    John Lutz was an American crime and mystery novelist best known for his suspenseful thrillers, several of which were adapted for film and television.
  • B. Gene L. Dodaro
    Gene L. Dodaro is an American public official who leads the U.S. Government Accountability Office as its chief auditor and oversight authority.
  • C. Phillip A. Talbert
    Phillip A. Talbert is a federal prosecutor who serves as the United States Attorney for the Eastern District of California.
  • D. Jeffrey B. Skiles
    Jeffrey B. Skiles is an American airline pilot best known as the first officer who helped successfully ditch US Airways Flight 1549 on the Hudson River in 2009.
  • E. William K. Reilly
    William K. Reilly is an American environmental leader and former Administrator of the U.S. Environmental Protection Agency known for his influential role in advancing environmental policy and conservation.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03edca064819081510bf303271062 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cf7ce7c8190810ef35b6e37254d completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:21 a.m.