Triple

T20306007
Position Surface form Disambiguated ID Type / Status
Subject Anjaneya E505609 entity
Predicate worshippedIn P2291 FINISHED
Object Thailand 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: Thailand | Statement: [Anjaneya, worshippedIn, Thailand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thailand
Context triple: [Anjaneya, worshippedIn, 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. Siam
    Siam was the former name of the kingdom that occupied the area of modern-day Thailand until it officially adopted the name "Thailand" in the 20th century.
  • C. 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.
  • D. 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.
  • E. Myanmar and Thailand
    Myanmar and Thailand are neighboring Southeast Asian countries that share a long land border, diverse cultures, and significant historical, economic, and geographic ties.
  • 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_69e0b4b8ab648190906e18538c250148 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6773f8f688190b616f972b9bbb28e completed April 20, 2026, 6:58 p.m.
Created at: April 16, 2026, 11:18 a.m.