Triple

T5283598
Position Surface form Disambiguated ID Type / Status
Subject Ngurah Rai International Airport E119556 entity
Predicate focusCityFor P164 FINISHED
Object Lion Air E296229 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: Lion Air | Statement: [Ngurah Rai International Airport, focusCityFor, Lion Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lion Air
Context triple: [Ngurah Rai International Airport, focusCityFor, Lion Air]
  • A. Lion Air chosen
    Lion Air is a major Indonesian low-cost airline operating extensive domestic and regional routes across Southeast Asia.
  • B. Sriwijaya Air
    Sriwijaya Air is an Indonesian airline that operates domestic and regional flights across Southeast Asia.
  • C. Garuda Indonesia
    Garuda Indonesia is the national flag carrier airline of Indonesia, operating domestic and international flights across Asia, Australia, the Middle East, and Europe.
  • D. Akasa Air
    Akasa Air is an Indian low-cost airline that began operations in 2022, offering domestic flights with a focus on affordable fares and a modern fleet.
  • E. 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.
  • 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_69bd446d05a8819092ad333a3f9c8d5c completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84c8d2bc8190840699e5a526b756 completed March 20, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf187d8a7c8190a8d686393d277bab completed March 21, 2026, 10:15 p.m.
Created at: March 20, 2026, 1:52 p.m.