Triple

T6353912
Position Surface form Disambiguated ID Type / Status
Subject Gili Islands E142942 entity
Predicate hasIsland P970 FINISHED
Object Gili Air E491239 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: Gili Air | Statement: [Gili Islands, hasIsland, Gili Air]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gili Air
Context triple: [Gili Islands, hasIsland, Gili Air]
  • A. Gili Air chosen
    Gili Air is a small Indonesian island near Lombok known for its laid-back atmosphere, coral reefs, and popular snorkeling and diving spots.
  • B. 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.
  • 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. 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.
  • 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_69c008d6dcbc8190aa1c2f1fd8916b42 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067dec4a88190992d57a0cc7782ad completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c60459a7c081909b551dcf1735bf75 completed March 27, 2026, 4:15 a.m.
Created at: March 22, 2026, 4:31 p.m.