Triple

T7523646
Position Surface form Disambiguated ID Type / Status
Subject Kawthaung E177836 entity
Predicate oppositeTown P16703 FINISHED
Object Ranong E178430 NE FINISHED

How this triple was built (3 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: Ranong | Statement: [Kawthaung, oppositeTown, Ranong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ranong
Context triple: [Kawthaung, oppositeTown, Ranong]
  • A. Ranong province chosen
    Ranong province is a coastal province in southern Thailand known for its mountainous rainforest terrain, high rainfall, and location along the Andaman Sea near the Myanmar border.
  • B. Tonsawang
    Tonsawang is an Austronesian language spoken by the Tonsawang people in North Sulawesi, Indonesia.
  • C. Thongduang
    Thongduang was the birth name of King Rama I of Siam, the founder and first monarch of Thailand’s Chakri Dynasty.
  • D. Mae Sot
    Mae Sot is a Thai border town in Tak Province known as a major hub for cross-border trade and migration with Myanmar and for its numerous refugee and humanitarian aid organizations.
  • E. Laem Chabang
    Laem Chabang is Thailand’s largest deep-sea commercial port and a major hub for maritime trade in Southeast Asia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: oppositeTown
Context triple: [Kawthaung, oppositeTown, Ranong]
  • A. oppositeCityCountry
    Indicates that a city and a country are located on opposite sides of the world or in geographically opposing regions relative to each other.
  • B. oppositeBankCity chosen
    Indicates that one city is located on the opposite bank of a river from another city.
  • C. opposite
    Indicates that one entity is positioned or oriented directly across from, or in a contrary or reverse relation to, another entity.
  • D. opposingLocation
    Indicates that two entities are located directly opposite each other, typically across a defined reference such as a street, corridor, or boundary.
  • E. hasTwinTown
    Indicates that two towns or cities are officially paired in a twinning relationship, typically for cultural, social, or economic exchange.
  • F. None of above.

Provenance (4 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_69c69f29bf3081909a146aec7755f185 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f7c4f32081908b5162f4551adb6d completed March 27, 2026, 9:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84efbbed48190baa687bb738a0c54 completed March 28, 2026, 9:58 p.m.
PD Predicate disambiguation batch_69c6f4d6bb808190bdd04499fd3bceb6 completed March 27, 2026, 9:21 p.m.
Created at: March 27, 2026, 3:46 p.m.