Triple

T3929332
Position Surface form Disambiguated ID Type / Status
Subject Phuket E93356 entity
Predicate majorCity P316 FINISHED
Object Phuket City E93356 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: Phuket City | Statement: [Phuket, majorCity, Phuket City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phuket City
Context triple: [Phuket, majorCity, Phuket City]
  • A. Phuket chosen
    Phuket is Thailand’s largest island and a major beach and resort destination in the Andaman Sea, renowned for its vibrant nightlife, coastal scenery, and role as a hub for cultural festivals and tourism.
  • B. Pattaya
    Pattaya is a major Thai coastal city known for its vibrant nightlife, beaches, and role as a leading international tourist resort.
  • C. Krabi
    Krabi is a coastal province in southern Thailand renowned for its dramatic limestone cliffs, clear turquoise waters, and island-hopping beaches like Railay and the Phi Phi Islands.
  • D. 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.
  • E. Patong Beach
    Patong Beach is Phuket’s most famous resort area, known for its long sandy shoreline, vibrant nightlife, and dense concentration of hotels, bars, and restaurants.
  • 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_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeeda65b708190b24cd715915aec1d completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53387775881909479f4e1fcecdaca completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:23 p.m.