Triple

T13912730
Position Surface form Disambiguated ID Type / Status
Subject Lady Thiang E334538 entity
Predicate setIn P1393 FINISHED
Object Siam 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: Siam | Statement: [Lady Thiang, setIn, Siam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Siam
Context triple: [Lady Thiang, setIn, Siam]
  • A. Siam
    Siam is a major commercial and transportation hub in central Bangkok, known for its large shopping complexes and role as a key interchange point in the city’s transit system.
  • B. 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.
  • C. 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.
  • D. Lithai
    Lithai was a prominent king of the Sukhothai Kingdom in 14th-century Thailand, known for consolidating royal power and promoting Theravada Buddhism and Thai culture.
  • E. Thái
    Thái is a Vietnamese family name commonly borne by individuals such as the military leader Hoàng Văn Thái.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de27245c648190b2946845ce0fdbf8 completed April 14, 2026, 11:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd192b5e508190b2d385657f9e358f completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:16 p.m.