Triple

T1017784
Position Surface form Disambiguated ID Type / Status
Subject Terry E21970 entity
Predicate hasOwner P347 FINISHED
Object Carl Spitz E211066 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: Carl Spitz | Statement: [Terry, hasOwner, Carl Spitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carl Spitz
Context triple: [Terry, hasOwner, Carl Spitz]
  • A. Carl Spitz chosen
    Carl Spitz was a renowned German-American dog trainer best known for training Toto in the classic film "The Wizard of Oz."
  • B. Charles Sporck
    Charles Sporck is an American engineer and executive best known for leading National Semiconductor to become a major force in the global semiconductor industry after an early career at Fairchild Semiconductor.
  • C. Carl Hagen
    Carl Hagen is an American theoretical physicist known for his role in developing the mechanism that predicted the Higgs boson and for contributions to quantum field theory.
  • D. Rudolf Garrels
    Rudolf Garrels was an 18th-century Dutch organ builder known for constructing and maintaining notable church organs in the Netherlands.
  • E. Walter Blume
    Walter Blume was a German aircraft designer and former World War I fighter ace best known for his work on advanced Luftwaffe aircraft during the Second World War.
  • 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_69a493c68e24819080ed0ee8bcfd5ce0 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7c4d488819081d8214ba0a22fe5 completed March 1, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf3a5cac081908d655e42a58a81c5 completed March 8, 2026, 10:09 p.m.
Created at: March 1, 2026, 7:41 p.m.