Triple

T12078233
Position Surface form Disambiguated ID Type / Status
Subject Kon-Tiki (2012 film) E287605 entity
Predicate filmingLocation P40 FINISHED
Object Thailand E5032 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: Thailand | Statement: [Kon-Tiki (2012 film), filmingLocation, Thailand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thailand
Context triple: [Kon-Tiki (2012 film), filmingLocation, Thailand]
  • A. Thailand chosen
    Thailand is a Southeast Asian nation known for its rich Buddhist culture, constitutional monarchy, and role as a regional hub for tourism and trade.
  • B. Saovabha Phongsri
    Saovabha Phongsri was a queen consort of Siam (Thailand), noted as one of King Chulalongkorn’s principal wives and the mother of several future Thai kings.
  • C. Thái
    Thái is a Vietnamese family name commonly borne by individuals such as the military leader Hoàng Văn Thái.
  • D. Myanmar
    Myanmar is a Southeast Asian nation bordered by India, China, and Thailand, known for its diverse ethnic groups, Buddhist heritage, and long history of military rule and political turmoil.
  • E. Laos
    Laos is a landlocked Southeast Asian country known for its mountainous terrain, Buddhist culture, and status as one of the region’s least developed but rapidly reforming economies.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9045e81f88190be2b1aabd93f077c completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f66301f081909697f9dd444a099e completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.