Triple

T5575470
Position Surface form Disambiguated ID Type / Status
Subject Dave Krusen E146306 entity
Predicate givenName P17 FINISHED
Object Dave E34737 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: Dave | Statement: [Dave Krusen, givenName, Dave]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dave
Context triple: [Dave Krusen, givenName, Dave]
  • A. Dave chosen
    Dave is a common masculine given name, often a shortened form of David, used widely in English-speaking countries.
  • B. Danny
    Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
  • C. Danny
    Danny is the charismatic, hard-drinking World War I veteran whose inherited houses and loose community of friends drive the picaresque adventures in John Steinbeck’s novel "Tortilla Flat."
  • D. Don
    The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
  • E. Don
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02067e8d8819090a006cb266da5fe completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d21ac6c81908a07c049d1ab81c6 completed March 22, 2026, 8:12 p.m.
Created at: March 22, 2026, 3:37 p.m.