Triple

T17790307
Position Surface form Disambiguated ID Type / Status
Subject Claire Cleary E444140 entity
Predicate loveInterestOf P7325 FINISHED
Object John Beckwith 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: John Beckwith | Statement: [Claire Cleary, loveInterestOf, John Beckwith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Beckwith
Context triple: [Claire Cleary, loveInterestOf, John Beckwith]
  • A. John Beckwith chosen
    John Beckwith is the charming, fast-talking divorce mediator and wedding crasher portrayed by Owen Wilson in the comedy film "Wedding Crashers."
  • B. Charles Bebb
    Charles Bebb was a prominent early 20th-century American architect based in Seattle, known for helping shape the city's skyline through major commercial and landmark buildings.
  • C. Samuel Beck
    Samuel Beck is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Beck.
  • D. Charles Alvin Beckwith
    Charles Alvin Beckwith was a highly decorated U.S. Army Special Forces officer best known for creating and leading the elite counterterrorism unit Delta Force.
  • E. John Sewell
    John Sewell is a former English footballer and manager best known for his involvement in North American soccer, including coaching in the NASL.
  • 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4879688908190a5428b1fa7525f62 completed April 19, 2026, 7:43 a.m.
Created at: April 10, 2026, 10:13 a.m.