Triple

T4597549
Position Surface form Disambiguated ID Type / Status
Subject Hendrik Lorentz E100240 entity
Predicate hasGivenName P17 FINISHED
Object Hendrik E104689 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: Hendrik | Statement: [Hendrik Lorentz, hasGivenName, Hendrik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hendrik
Context triple: [Hendrik Lorentz, hasGivenName, Hendrik]
  • A. Hendrik chosen
    Hendrik is a masculine given name of Germanic origin, commonly used in Dutch- and German-speaking countries and related to the name Henry.
  • B. Willem
    Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
  • C. Adriaan
    Adriaan is a masculine given name of Dutch origin commonly used in the Netherlands and other Dutch-speaking regions.
  • D. Dirck
    Dirck is a Dutch masculine given name historically borne by several notable figures, including artists of the Dutch Golden Age.
  • E. Hendrika
    Hendrika is a feminine given name of Dutch origin, commonly used in the Netherlands and related to the name Hendrickje.
  • 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_69bd43cbc014819098b45f435908f88a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd59420c108190b5c2c5039e964da5 completed March 20, 2026, 2:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa4f26d08190b9978c579623adcb completed March 21, 2026, 1:54 a.m.
Created at: March 20, 2026, 1:11 p.m.