Triple

T2907001
Position Surface form Disambiguated ID Type / Status
Subject Tupolev Tu-134 E62789 entity
Predicate usedBy P260 FINISHED
Object CSA Czechoslovak Airlines E33033 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: CSA Czechoslovak Airlines | Statement: [Tupolev Tu-134, usedBy, CSA Czechoslovak Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CSA Czechoslovak Airlines
Context triple: [Tupolev Tu-134, usedBy, CSA Czechoslovak Airlines]
  • A. Czech Airlines chosen
    Czech Airlines is the national flag carrier of the Czech Republic, operating scheduled passenger flights across Europe and to select long-haul destinations.
  • B. Malev Hungarian Airlines
    Malev Hungarian Airlines was the former national flag carrier of Hungary, operating scheduled passenger flights across Europe and beyond until its closure in 2012.
  • C. Austrian Airlines
    Austrian Airlines is the flag carrier airline of Austria, operating an extensive network of European and long-haul flights from its main hub in Vienna.
  • D. Swissair
    Swissair was the former national airline of Switzerland, renowned for its high service standards and extensive international route network until its collapse in 2001.
  • E. S7 Airlines
    S7 Airlines is a major Russian airline based in Novosibirsk that operates extensive domestic and international routes, particularly across Russia, Europe, and Asia.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0d0628c81909680af2f0db2ecae completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b08658407c8190ad7798590dd17ef9 completed March 10, 2026, 9 p.m.
Created at: March 6, 2026, 10:11 p.m.