Triple

T4968722
Position Surface form Disambiguated ID Type / Status
Subject Rebekka Vaark E111590 entity
Predicate hasSpouse P13 FINISHED
Object Jacob Vaark E122798 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: Jacob Vaark | Statement: [Rebekka Vaark, hasSpouse, Jacob Vaark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jacob Vaark
Context triple: [Rebekka Vaark, hasSpouse, Jacob Vaark]
  • A. Jacob Vaark chosen
    Jacob Vaark is a 17th-century Anglo-Dutch farmer and landowner in Toni Morrison’s novel "A Mercy," whose experiences reflect the brutal complexities of early American colonialism and slavery.
  • B. Johan Evertsen
    Johan Evertsen was a prominent 17th-century Dutch admiral who played a key role in the naval conflicts of the Dutch Republic, including the Anglo-Dutch Wars.
  • C. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • D. Johan
    Johan is the given first name of the Swedish playwright and novelist August Strindberg.
  • E. Jost Vacano
    Jost Vacano is a German cinematographer renowned for his dynamic, technically innovative work on films such as "Das Boot," "RoboCop," and other major international productions.
  • 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_69bd441a0eb481908050fa4273b19eae completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7210c8f081908e36595a12d07f64 completed March 20, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89fddbb8819084c8c21ee0ce845e completed March 21, 2026, 12:07 p.m.
Created at: March 20, 2026, 1:32 p.m.