Triple

T5501184
Position Surface form Disambiguated ID Type / Status
Subject Dave Hakstol E144331 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 Hakstol, givenName, Dave]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dave
Context triple: [Dave Hakstol, 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
    Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
  • E. 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.
  • 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_69c008f5a2748190bce7a39aabf87a6d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f08c2a4819093e772a1497c7ecc completed March 22, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027a10fa08190853d45354fd9b044 completed March 22, 2026, 5:32 p.m.
Created at: March 22, 2026, 3:32 p.m.