Triple

T15985068
Position Surface form Disambiguated ID Type / Status
Subject Samuel Fischer E387670 entity
Predicate placeOfBirth P1 FINISHED
Object Liptóújvár E948761 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: Liptóújvár | Statement: [Samuel Fischer, placeOfBirth, Liptóújvár]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liptóújvár
Context triple: [Samuel Fischer, placeOfBirth, Liptóújvár]
  • A. Liptó chosen
    Liptó is a historical region in northern Hungary (now largely in Slovakia), known for its mountainous landscape and traditional Hungarian and Slovak cultural heritage.
  • B. Ungvár
    Ungvár is the historical Hungarian name for the city now known as Uzhhorod, a regional center in western Ukraine near the Slovak border.
  • C. Tiszavasvári
    Tiszavasvári is a town in northeastern Hungary known for its agricultural surroundings and location within the Northern Great Plain region.
  • D. Kozármisleny
    Kozármisleny is a small town in southern Hungary, near Pécs, known for its growing residential character and local sports culture.
  • E. Csákvár
    Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15757a3548190900de1962308f6b8 completed April 16, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3cdf7848190848e9081027dc027 completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:54 a.m.