Triple

T12231744
Position Surface form Disambiguated ID Type / Status
Subject Sentry E291491 entity
Predicate realName P9233 FINISHED
Object Robert Reynolds E529965 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: Robert Reynolds | Statement: [Sentry, realName, Robert Reynolds]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Reynolds
Context triple: [Sentry, realName, Robert Reynolds]
  • A. Robert Reynolds chosen
    Robert Reynolds is a common personal name shared by multiple notable individuals across fields such as entertainment, sports, and academia.
  • B. Roger Reeves
    Roger Reeves is an American worker best known as the plaintiff in the landmark U.S. Supreme Court age discrimination case Reeves v. Sanderson Plumbing Products, Inc.
  • C. Jeremy Reeves
    Jeremy Reeves is an American songwriter and producer best known as a member of the Grammy-winning production team The Stereotypes, recognized for crafting hits for major pop and R&B artists.
  • D. Michael Parks
    Michael Parks was an American character actor known for his intense, versatile performances in film and television, including frequent collaborations with directors like Quentin Tarantino and Kevin Smith.
  • E. Scott Reed
    Scott Reed is a computer scientist and machine learning researcher known for his work on deep learning and generative models.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca45bd48190b8b7f6b29b6bb25b completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60aad2d488190ba36588e3376ca1a completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:51 p.m.