Triple

T14930099
Position Surface form Disambiguated ID Type / Status
Subject József Kauser E372237 entity
Predicate nameInNativeLanguage P1435 FINISHED
Object Kauser József E372237 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: Kauser József | Statement: [József Kauser, nameInNativeLanguage, Kauser József]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kauser József
Context triple: [József Kauser, nameInNativeLanguage, Kauser József]
  • A. József Kauser chosen
    József Kauser was a Hungarian architect best known for his significant role in completing and shaping the design of Budapest’s monumental St. Stephen's Basilica.
  • B. Miklós László
    Miklós László was a Hungarian-born playwright best known for writing the stage play that inspired the classic film "The Shop Around the Corner."
  • C. Pál Kadosa
    Pál Kadosa was a Hungarian pianist, composer, and influential music educator known for his contributions to 20th-century Hungarian classical music.
  • D. József Takács
    József Takács is a Hungarian footballer known for his contributions to early 20th-century Hungarian club and national teams.
  • E. János Józsa
    János Józsa is a Hungarian academic and engineer who has served as rector of the Budapest University of Technology and Economics.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded64550dc8190ba44120df00ba498 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01d44044819088c86f46b02404ed completed May 9, 2026, 9:43 a.m.
Created at: April 10, 2026, 2:36 a.m.