Triple

T26641057
Position Surface form Disambiguated ID Type / Status
Subject ยี่เป็ง E668779 entity
Predicate จัดขึ้นเด่นชัดในจังหวัด P100087 FINISHED
Object ลำพูน
ลำพูนเป็นจังหวัดเก่าแก่ในภาคเหนือของประเทศไทยที่มีวัฒนธรรมล้านนาเข้มข้นและบรรยากาศเงียบสงบไม่พลุกพล่านเหมือนเมืองท่องเที่ยวใหญ่ใกล้เคียงอย่างเชียงใหม่
 E1736485 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: ลำพูน | Statement: [ยี่เป็ง, จัดขึ้นเด่นชัดในจังหวัด, ลำพูน]
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: ลำพูน
Triple: [ยี่เป็ง, จัดขึ้นเด่นชัดในจังหวัด, ลำพูน]
Generated description
ลำพูนเป็นจังหวัดเก่าแก่ในภาคเหนือของประเทศไทยที่มีวัฒนธรรมล้านนาเข้มข้นและบรรยากาศเงียบสงบไม่พลุกพล่านเหมือนเมืองท่องเที่ยวใหญ่ใกล้เคียงอย่างเชียงใหม่
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: จัดขึ้นเด่นชัดในจังหวัด
Context triple: [ยี่เป็ง, จัดขึ้นเด่นชัดในจังหวัด, ลำพูน]
  • A. heldInProvince chosen
    Indicates that an event or activity takes place within the boundaries of a specified province.
  • B. tookPlaceInState
    Indicates that an event or occurrence happened within the geographical or political boundaries of a specific state.
  • C. stationedInProvince
    Indicates that an entity is assigned or based in a particular province as its location or area of operation.
  • D. concentratedInProvince
    Indicates that something is primarily located, focused, or densely present within a particular province.
  • E. operatedVenueProvince
    Indicates that an entity operated a venue located within a specified province.
  • F. None of above.

Provenance (6 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_69ee9d0024b8819090a7c8cf669a3b6c completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f61fd623bc819091df736cf3419b99 completed May 2, 2026, 4:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec3f176c819093139c14525c7df5 completed May 23, 2026, 6:04 p.m.
NEDg Description generation batch_6a11f74329f48190a78ce3f209f8a134 completed May 23, 2026, 6:51 p.m.
NED2 Entity disambiguation (via description) batch_6a11f7d911448190ae1b41d1cff8a85e completed May 23, 2026, 6:54 p.m.
PD Predicate disambiguation batch_69f61b3d23f481908dfec27adace900a completed May 2, 2026, 3:41 p.m.
Created at: April 27, 2026, 2:29 a.m.