Triple

T14126101
Position Surface form Disambiguated ID Type / Status
Subject Robert Blees E340037 entity
Predicate name P16 FINISHED
Object Robert Blees E340037 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 Blees | Statement: [Robert Blees, name, Robert Blees]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Blees
Context triple: [Robert Blees, name, Robert Blees]
  • A. Robert Blees chosen
    Robert Blees was an American screenwriter and producer known for his work on mid-20th-century Hollywood films and television series.
  • B. Leonard Bleecker
    Leonard Bleecker was an early American broker and financier known for being among the original founders of what became the New York Stock Exchange.
  • C. Edward Leede
    Edward Leede was a notable Dartmouth College basketball player and benefactor after whom Dartmouth’s Leede Arena is named.
  • D. Marshall Blechtman
    Marshall Blechtman is a quirky, socially awkward high school student and one of the central teen characters in the early-1980s sitcom "Square Pegs."
  • E. Joseph Weishaar
    Joseph Weishaar is an American architect and designer best known for winning the competition to create the National World War I Memorial in Washington, D.C.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6096976481909dc79066c5165a50 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7e2b0248190ba40aa8395355052 completed May 7, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:22 p.m.