Triple

T19465263
Position Surface form Disambiguated ID Type / Status
Subject Daniel Bissell Jr. E486978 entity
Predicate familyName P18 FINISHED
Object Bissell 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: Bissell | Statement: [Daniel Bissell Jr., familyName, Bissell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bissell
Context triple: [Daniel Bissell Jr., familyName, Bissell]
  • A. Bissell chosen
    Bissell is a surname most notably associated with American intelligence official Richard M. Bissell Jr., a key figure in early CIA covert operations.
  • B. Bissell Bridge
    Bissell Bridge is a highway bridge in Connecticut that carries traffic across the Connecticut River between East Hartford and Windsor.
  • C. iRobot
    iRobot is an American technology company best known for creating the Roomba line of autonomous robotic vacuum cleaners and other consumer robots.
  • D. Dyson
    Dyson is a surname most famously associated with theoretical physicist and mathematician Freeman Dyson, known for his influential work in quantum electrodynamics and futurism.
  • E. Valetudo
    Valetudo is a small, irregular outer moon of Jupiter with a distant, inclined orbit that makes it one of the planet’s more recently discovered natural satellites.
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633d0fe3c8190b637f78bfad704d0 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:39 p.m.