Triple

T5918221
Position Surface form Disambiguated ID Type / Status
Subject Lara's Theme E131633 entity
Predicate authorOfSourceWork P2353 FINISHED
Object Boris Pasternak E81170 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: Boris Pasternak | Statement: [Lara's Theme, authorOfSourceWork, Boris Pasternak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boris Pasternak
Context triple: [Lara's Theme, authorOfSourceWork, Boris Pasternak]
  • A. Boris Pasternak chosen
    Boris Pasternak was a Russian poet and novelist best known internationally for his novel "Doctor Zhivago," which earned him the Nobel Prize in Literature in 1958.
  • B. Leonid Pasternak
    Leonid Pasternak was a Russian Impressionist painter and illustrator known for his portraits and his association with the literary and artistic circles of late Imperial Russia.
  • C. Peter Pasternak
    Peter Pasternak is known primarily as the son of famed Hollywood film producer Joe Pasternak.
  • D. Ivan Bunin
    Ivan Bunin was a Russian writer and poet, renowned for his masterful prose and as the first Russian recipient of the Nobel Prize in Literature.
  • E. Joe Pasternak
    Joe Pasternak was a prominent Hollywood film producer best known for his successful musicals and light comedies from the 1930s through the 1950s.
  • 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c037feb9d8819089bf68e3a4a53534 completed March 22, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e39ea48c8190a968f81f0e26ccbf completed March 23, 2026, 6:54 a.m.
Created at: March 22, 2026, 3:59 p.m.