Triple

T4896643
Position Surface form Disambiguated ID Type / Status
Subject Orient Express E109698 entity
Predicate countryServed P1083 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: [Orient Express, countryServed, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hungary
Context triple: [Orient Express, countryServed, 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. Ungar
    Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
  • C. Slovakia and Hungary
    Slovakia and Hungary are neighboring Central European countries that share a significant stretch of their border along the Danube River.
  • D. 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.
  • E. 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.
  • 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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e2923a081909bd592880b6f399b completed March 20, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fb5da2c8190aeec7d6d11b12b11 completed March 21, 2026, 10:15 a.m.
Created at: March 20, 2026, 1:28 p.m.