Triple

T7762220
Position Surface form Disambiguated ID Type / Status
Subject Phang Nga province E176050 entity
Predicate hasBeachArea P1922 FINISHED
Object Khao Lak E394556 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: Khao Lak | Statement: [Phang Nga province, hasBeachArea, Khao Lak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khao Lak
Context triple: [Phang Nga province, hasBeachArea, Khao Lak]
  • A. Khao Lak chosen
    Khao Lak is a coastal resort area in southern Thailand known for its tranquil beaches, proximity to national parks, and devastation during the 2004 Indian Ocean tsunami.
  • B. Lamphun
    Lamphun is a historic provincial capital in northern Thailand, known for its ancient Hariphunchai kingdom heritage and well-preserved temples.
  • C. Phitsanulok
    Phitsanulok is a historic provincial city in northern Thailand known as a regional transport hub and home to the revered Wat Phra Si Rattana Mahathat temple.
  • D. Chiang Rai
    Chiang Rai is a culturally rich city in far northern Thailand, known for its temples, hill-tribe communities, and role as a gateway to the Golden Triangle region.
  • E. Chachoengsao
    Chachoengsao is a province in eastern Thailand known for its historic temples, agricultural landscape, and proximity to Bangkok and major transport hubs.
  • 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_69c69962923c8190ac74d28b4f9fe0a0 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70404c2108190ad2b900ac9bf582b completed March 27, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ca392955f081909deeeae20822adc0 completed March 30, 2026, 8:49 a.m.
Created at: March 27, 2026, 4:09 p.m.