Triple

T1965204
Position Surface form Disambiguated ID Type / Status
Subject 1848 revolutions E42671 entity
Predicate location P40 FINISHED
Object Hungary E5017 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: Hungary | Statement: [1848 revolutions, location, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hungary
Context triple: [1848 revolutions, location, Hungary]
  • A. Hungary chosen
    Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
  • B. Slovakia and Hungary
    Slovakia and Hungary are neighboring Central European countries that share a significant stretch of their border along the Danube River.
  • C. Austria
    Austria is a landlocked Central European country known for its Alpine landscapes, rich cultural and musical heritage, and status as a prosperous, democratic member of the European Union.
  • D. Slovakia
    Slovakia is a landlocked Central European country known for its mountainous landscapes, medieval castles, and membership in major international organizations such as the European Union and NATO.
  • E. Romania
    Romania is a southeastern European country known for its role in World War II, its Carpathian mountain landscapes, and its historical regions such as Transylvania.
  • 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_69a88711151c8190940b2572095059d7 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb3aeb20081908b0d447d9fcdbaad completed March 7, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb96d12481908f8d7d5c9f1f103f completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:36 p.m.