Triple

T5351345
Position Surface form Disambiguated ID Type / Status
Subject Julie Kafka E102584 entity
Predicate child P120 FINISHED
Object Franz Kafka E18045 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: Franz Kafka | Statement: [Julie Kafka, child, Franz Kafka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franz Kafka
Context triple: [Julie Kafka, child, Franz Kafka]
  • A. Franz Kafka chosen
    Franz Kafka was a 20th-century Bohemian novelist and short-story writer whose surreal, existential works like "The Metamorphosis" and "The Trial" profoundly shaped modern literature.
  • B. Gabriele Kafka
    Gabriele Kafka was one of Franz Kafka’s sisters, a member of the Kafka family in early 20th-century Prague.
  • C. Hermann Kafka
    Hermann Kafka was a Prague businessman and the domineering father of writer Franz Kafka, whose difficult relationship with his son deeply influenced Franz's life and work.
  • D. Ottla Kafka
    Ottla Kafka was the youngest sister of writer Franz Kafka, known from his diaries and letters for their close relationship and her later persecution and death in the Holocaust.
  • E. Jaroslav Hašek
    Jaroslav Hašek was a Czech writer and satirist best known for his unfinished comic novel "The Good Soldier Švejk," a classic of anti-war literature.
  • 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_69bd43d8f7248190b64c140734b5c9a8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd861188ac81908ef2b1f25cc6c864 completed March 20, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf291610b4819086e04f232e4eba7d completed March 21, 2026, 11:26 p.m.
Created at: March 20, 2026, 2:01 p.m.