Triple

T17603543
Position Surface form Disambiguated ID Type / Status
Subject Rudolf Beran E428766 entity
Predicate familyName P18 FINISHED
Object Beran NE NERFINISHED

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: Beran | Statement: [Rudolf Beran, familyName, Beran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beran
Context triple: [Rudolf Beran, familyName, Beran]
  • A. Beran chosen
    Beran is a Czech surname most notably borne by Rudolf Beran, a prominent Czechoslovak politician and prime minister before and during the early years of World War II.
  • B. Beránek
    Beránek is a Czech surname and word meaning "little lamb," commonly used as a family name in Czech-speaking regions.
  • C. Vamberk
    Vamberk is a Czech town in the Hradec Králové Region renowned for its long tradition of handmade bobbin lace-making.
  • D. Melinka
    Melinka is a small coastal town in southern Chile that serves as the main settlement and administrative center of the remote Guaitecas Archipelago.
  • E. Zamberk
    Zamberk is a small historic town in the Pardubice Region of the Czech Republic, known for its traditional architecture and scenic setting in the Orlické Mountains foothills.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c4a9a948190bc857f5da9dc7444 completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.