Triple

T12870553
Position Surface form Disambiguated ID Type / Status
Subject Ban Pong E307837 entity
Predicate connectedToByRail P71547 FINISHED
Object Kanchanaburi E680666 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: Kanchanaburi | Statement: [Ban Pong, connectedToByRail, Kanchanaburi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanchanaburi
Context triple: [Ban Pong, connectedToByRail, Kanchanaburi]
  • A. Kanchanaburi Province chosen
    Kanchanaburi Province is a western Thai province known for its mountainous landscapes, national parks, and historic sites such as the Bridge over the River Kwai.
  • B. Sangkhlaburi
    Sangkhlaburi is a remote Thai town near the Myanmar border, known for its cultural mix of Thai, Mon, and Karen communities and its iconic wooden Mon Bridge over the Songkalia River.
  • C. Suphan Buri
    Suphan Buri is a province in central Thailand known for its rich history, traditional culture, and agricultural landscapes.
  • D. Khura Buri
    Khura Buri is a coastal town in southern Thailand known as a gateway to nearby islands and marine national parks in the Andaman Sea.
  • E. Phetchaburi
    Phetchaburi is a historic city in western Thailand known for its ancient temples, royal palaces, and proximity to coastal and mountainous attractions.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970905784819091631161a9de98c5 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a55161a881908d767653c17d3acc completed May 3, 2026, 1:30 a.m.
Created at: April 9, 2026, 5:38 p.m.