Triple

T22454901
Position Surface form Disambiguated ID Type / Status
Subject Sultan Hasanuddin International Airport E555089 entity
Predicate servesAsHubFor P423 FINISHED
Object Lion Air NE NERFINISHED

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: [Sultan Hasanuddin International Airport, servesAsHubFor, Lion Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lion Air
Context triple: [Sultan Hasanuddin International Airport, servesAsHubFor, 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. Merpati Nusantara Airlines
    Merpati Nusantara Airlines was an Indonesian state-owned airline that operated domestic and regional flights across the archipelago before ceasing operations.
  • C. Sriwijaya Air
    Sriwijaya Air is an Indonesian airline that operates domestic and regional flights across Southeast Asia.
  • D. Mandala Airlines
    Mandala Airlines was an Indonesian airline that operated domestic and regional flights before ceasing operations in the early 2010s.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b4e2bd4819083e5bed44e9776c6 completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:48 p.m.