Triple

T10456917
Position Surface form Disambiguated ID Type / Status
Subject Nong Khai E246572 entity
Predicate oppositeBankCity P16703 FINISHED
Object Tha Na Laeng
Tha Na Laeng is a town in Laos located across the Mekong River from Nong Khai, Thailand, serving as a key cross-border transit point between the two countries.
 E864413 NE FINISHED

How this triple was built (4 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: Tha Na Laeng | Statement: [Nong Khai, oppositeBankCity, Tha Na Laeng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tha Na Laeng
Context triple: [Nong Khai, oppositeBankCity, Tha Na Laeng]
  • A. Thakoon
    Thakoon is a New York-based fashion label founded by designer Thakoon Panichgul, known for its modern, feminine ready-to-wear collections and innovative prints.
  • B. Longleng
    Longleng is a town and administrative center in the northeastern Indian state of Nagaland, known as the headquarters of Longleng district.
  • C. Guting
    Guting is a key Taipei Metro station in central Taipei that serves as a transfer point between multiple subway lines.
  • D. Laoang
    Laoang is a coastal municipality in the province of Northern Samar in the Philippines, known for its island landscapes and fishing communities.
  • E. Lun Tha
    Lun Tha is a romantic male lead in the musical "The King and I," known for his forbidden love affair with Tuptim.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tha Na Laeng
Triple: [Nong Khai, oppositeBankCity, Tha Na Laeng]
Generated description
Tha Na Laeng is a town in Laos located across the Mekong River from Nong Khai, Thailand, serving as a key cross-border transit point between the two countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tha Na Laeng
Target entity description: Tha Na Laeng is a town in Laos located across the Mekong River from Nong Khai, Thailand, serving as a key cross-border transit point between the two countries.
  • A. Thakoon
    Thakoon is a New York-based fashion label founded by designer Thakoon Panichgul, known for its modern, feminine ready-to-wear collections and innovative prints.
  • B. Longleng
    Longleng is a town and administrative center in the northeastern Indian state of Nagaland, known as the headquarters of Longleng district.
  • C. Guting
    Guting is a key Taipei Metro station in central Taipei that serves as a transfer point between multiple subway lines.
  • D. Laoang
    Laoang is a coastal municipality in the province of Northern Samar in the Philippines, known for its island landscapes and fishing communities.
  • E. Lun Tha
    Lun Tha is a romantic male lead in the musical "The King and I," known for his forbidden love affair with Tuptim.
  • F. None of above. chosen

Provenance (5 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe498a808190b88530f0221df4a6 completed April 7, 2026, 12:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87f10b45c81908f1d3128c65750f8 completed April 10, 2026, 4:39 a.m.
NEDg Description generation batch_69d886c64e008190a914b66be16566d1 completed April 10, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d88dd0c28481908008aea09bf956ca completed April 10, 2026, 5:42 a.m.
Created at: April 6, 2026, 12:18 p.m.