Triple

T16464201
Position Surface form Disambiguated ID Type / Status
Subject Phuket Province E399886 entity
Predicate hasCity 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 Province, hasCity, Phuket City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phuket City
Context triple: [Phuket Province, hasCity, 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. Hua Hin
    Hua Hin is a popular seaside resort town on the Gulf of Thailand, known for its beaches, royal residences, and relaxed coastal atmosphere.
  • C. Pattaya
    Pattaya is a major Thai coastal city known for its vibrant nightlife, beaches, and role as a leading international tourist resort.
  • D. 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.
  • E. 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.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d83687081908450657e1da6f6af completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0091872e648190b805aa4e41bcbb6d completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:10 a.m.