Triple

T1783144
Position Surface form Disambiguated ID Type / Status
Subject Perak E39332 entity
Predicate containsTown P847 FINISHED
Object Taiping
Taiping is a historic town in the Malaysian state of Perak, known for its colonial-era architecture, lush lake gardens, and high annual rainfall.
 E198099 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: Taiping | Statement: [Perak, containsTown, Taiping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taiping
Context triple: [Perak, containsTown, Taiping]
  • A. Taiping Heavenly Kingdom
    The Taiping Heavenly Kingdom was a massive mid-19th-century Chinese rebel state and millenarian theocracy that waged the devastating Taiping Rebellion against the Qing dynasty.
  • B. Fengtian
    Fengtian is the historical name of Shenyang, a major city in northeastern China that has long served as a political and economic center of the region.
  • C. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • D. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • E. Wei-kuo
    Wei-kuo is the given name of Chiang Wei-kuo, a Chinese military officer and adopted son of Chiang Kai-shek who served in both German and later Republic of China forces.
  • 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: Taiping
Triple: [Perak, containsTown, Taiping]
Generated description
Taiping is a historic town in the Malaysian state of Perak, known for its colonial-era architecture, lush lake gardens, and high annual rainfall.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taiping
Target entity description: Taiping is a historic town in the Malaysian state of Perak, known for its colonial-era architecture, lush lake gardens, and high annual rainfall.
  • A. Taiping Heavenly Kingdom
    The Taiping Heavenly Kingdom was a massive mid-19th-century Chinese rebel state and millenarian theocracy that waged the devastating Taiping Rebellion against the Qing dynasty.
  • B. Fengtian
    Fengtian is the historical name of Shenyang, a major city in northeastern China that has long served as a political and economic center of the region.
  • C. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • D. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • E. Wei-kuo
    Wei-kuo is the given name of Chiang Wei-kuo, a Chinese military officer and adopted son of Chiang Kai-shek who served in both German and later Republic of China forces.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e4cf108190891338052b581ae8 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada9a1aa8481908cbcecde85804461 completed March 8, 2026, 4:53 p.m.
NEDg Description generation batch_69adab04b5688190afb3418e9b9da845 completed March 8, 2026, 4:59 p.m.
NED2 Entity disambiguation (via description) batch_69adaeb20390819098bad8951ec00d00 completed March 8, 2026, 5:15 p.m.
Created at: March 4, 2026, 7:31 p.m.