Triple

T18934129
Position Surface form Disambiguated ID Type / Status
Subject Michael Benaroya E463194 entity
Predicate notableWork P4 FINISHED
Object Cell NE NERFINISHED

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: Cell | Statement: [Michael Benaroya, notableWork, Cell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cell
Context triple: [Michael Benaroya, notableWork, Cell]
  • A. Cell chosen
    "Cell" is a horror novel by Stephen King that follows a group of survivors navigating a post-apocalyptic world after a mysterious signal transmitted through cell phones turns people into violent killers.
  • B. Cell
    Cell is a leading peer-reviewed scientific journal that publishes high-impact research across the life sciences, particularly in molecular and cellular biology.
  • C. Cell
    Cell is a major bio-engineered villain in Dragon Ball Z who possesses the abilities of multiple characters and seeks perfection through absorbing others.
  • D. Cells
    Cells is a series of large-scale sculptural installations by Louise Bourgeois that explore themes of memory, trauma, and the body through enclosed, room-like structures filled with symbolic objects.
  • E. Cell 211
    Cell 211 is a critically acclaimed Spanish prison thriller film centered on a deadly riot and the moral dilemmas it creates.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcfec90481909e926be9767e5779 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d3e57e648190aa4d3b09e84d4d38 completed April 20, 2026, 7:21 a.m.
Created at: April 10, 2026, 11:59 a.m.