Triple

T4724114
Position Surface form Disambiguated ID Type / Status
Subject Gabriele Kafka E104838 entity
Predicate familyName P18 FINISHED
Object Kafka E104838 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: Kafka | Statement: [Gabriele Kafka, familyName, Kafka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kafka
Context triple: [Gabriele Kafka, familyName, Kafka]
  • A. Gabriele Kafka chosen
    Gabriele Kafka was one of Franz Kafka’s sisters, a member of the Kafka family in early 20th-century Prague.
  • B. Franz Kafka
    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.
  • C. 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.
  • D. Julie Kafka
    Julie Kafka was the mother of renowned writer Franz Kafka and a member of a middle-class Jewish family in Prague.
  • E. Kafka on the Shore
    Kafka on the Shore is a surreal, genre-blending novel by Haruki Murakami that intertwines the journeys of a runaway teenager and an elderly man who can talk to cats in a dreamlike exploration of memory, fate, and identity.
  • 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_69bd43ed84648190ae0b7ee8e8d00482 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6444412c81908a7f6f17978df2d2 completed March 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be10986d688190ad82e7f959c50434 completed March 21, 2026, 3:29 a.m.
Created at: March 20, 2026, 1:18 p.m.