Triple

T1722004
Position Surface form Disambiguated ID Type / Status
Subject Airbus A300 E37411 entity
Predicate usedBy P260 FINISHED
Object Garuda Indonesia E30719 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: Garuda Indonesia | Statement: [Airbus A300, usedBy, Garuda Indonesia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garuda Indonesia
Context triple: [Airbus A300, usedBy, Garuda Indonesia]
  • A. Garuda Indonesia chosen
    Garuda Indonesia is the national flag carrier airline of Indonesia, operating domestic and international flights across Asia, Australia, the Middle East, and Europe.
  • B. IndiGo
    IndiGo is a major Indian low-cost airline known for its extensive domestic network, high on-time performance, and large fleet of Airbus A320-family aircraft.
  • C. Malaysia Airlines
    Malaysia Airlines is the flag carrier of Malaysia, operating international and domestic flights across Asia, Europe, and other regions from its main hub in Kuala Lumpur.
  • D. Malaysia Aviation Group
    Malaysia Aviation Group is a Malaysian state-owned aviation holding company that oversees Malaysia Airlines and several related aviation and travel businesses.
  • E. EVA Air
    EVA Air is a major Taiwanese international airline known for its extensive global route network, high service standards, and innovative themed flights such as its Hello Kitty jets.
  • 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_69a8861acab88190bb43cde203429399 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa635703dc8190809260de43b72ea3 completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8aeca12881908efad5991bb0f12b completed March 8, 2026, 2:42 p.m.
Created at: March 4, 2026, 7:30 p.m.