Triple

T12474507
Position Surface form Disambiguated ID Type / Status
Subject Kangaroo Route E298140 entity
Predicate typicalStopoversHistorically P43132 FINISHED
Object Bangkok E10237 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: Bangkok | Statement: [Kangaroo Route, typicalStopoversHistorically, Bangkok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangkok
Context triple: [Kangaroo Route, typicalStopoversHistorically, Bangkok]
  • A. Bangkok chosen
    Bangkok is the vibrant capital and largest city of Thailand, known for its bustling street life, ornate temples, and role as a major economic and cultural hub in Southeast Asia.
  • B. Pattaya
    Pattaya is a major Thai coastal city known for its vibrant nightlife, beaches, and role as a leading international tourist resort.
  • C. Hat Yai
    Hat Yai is a major commercial and transportation hub city in southern Thailand, known for its bustling markets and proximity to the Malaysian border.
  • D. Chiang Mai
    Chiang Mai is a historic city in northern Thailand known for its ancient temples, vibrant night markets, and surrounding mountainous landscapes.
  • E. Seoul–Bangkok
    Seoul–Bangkok is a major international air route connecting the capital cities of South Korea and Thailand, popular for both tourism and business travel.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541ace208190a5149b6f18fa196d completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f0ea1e48190a11cf94797290156 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.