Triple

T1333207
Position Surface form Disambiguated ID Type / Status
Subject Southern Thailand E28689 entity
Predicate hasMajorCity P316 FINISHED
Object Yala
Yala is a major city in Thailand’s deep south, known as an administrative, commercial, and cultural center near the Malaysian border.
 E151102 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: Yala | Statement: [Southern Thailand, hasMajorCity, Yala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yala
Context triple: [Southern Thailand, hasMajorCity, Yala]
  • A. Gela Sule
    Gela Sule is a variant name for Nggela Sule, a locality associated with the Nggela (Florida) Islands in the Solomon Islands.
  • B. Al Bayda
    Al Bayda is a city in northeastern Libya that serves as one of the main urban centers of the Cyrenaica region.
  • C. Berbera
    Berbera is a major port city on the Gulf of Aden in Somaliland, serving as a key maritime hub for trade in the Horn of Africa.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Kufa
    Kufa is an ancient Iraqi city that became an early Islamic cultural and religious center, historically renowned as a hub of scholarship and calligraphy.
  • 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: Yala
Triple: [Southern Thailand, hasMajorCity, Yala]
Generated description
Yala is a major city in Thailand’s deep south, known as an administrative, commercial, and cultural center near the Malaysian border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yala
Target entity description: Yala is a major city in Thailand’s deep south, known as an administrative, commercial, and cultural center near the Malaysian border.
  • A. Gela Sule
    Gela Sule is a variant name for Nggela Sule, a locality associated with the Nggela (Florida) Islands in the Solomon Islands.
  • B. Al Bayda
    Al Bayda is a city in northeastern Libya that serves as one of the main urban centers of the Cyrenaica region.
  • C. Berbera
    Berbera is a major port city on the Gulf of Aden in Somaliland, serving as a key maritime hub for trade in the Horn of Africa.
  • D. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • E. Kufa
    Kufa is an ancient Iraqi city that became an early Islamic cultural and religious center, historically renowned as a hub of scholarship and calligraphy.
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1e98900819092c54c0fb58b958a completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf383b24819092acd076130ca5c0 completed March 8, 2026, 12:13 a.m.
NEDg Description generation batch_69acbf77a3748190a510ea10d8ae4373 completed March 8, 2026, 12:14 a.m.
NED2 Entity disambiguation (via description) batch_69acbfe5eae88190ba65808402ada37f completed March 8, 2026, 12:16 a.m.
Created at: March 1, 2026, 7:55 p.m.