Triple

T1834702
Position Surface form Disambiguated ID Type / Status
Subject Xiaogan E41038 entity
Predicate administrativeDivision P747 FINISHED
Object Anlu
Anlu is a county-level city in central China's Hubei province, known for its historical significance and agricultural economy.
 E206627 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: Anlu | Statement: [Xiaogan, administrativeDivision, Anlu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Anlu
Context triple: [Xiaogan, administrativeDivision, Anlu]
  • A. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • B. Guguan
    Guguan is an uninhabited volcanic island in the Northern Mariana Islands chain in the western Pacific Ocean.
  • C. Jianye
    Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
  • D. Luyang
    Luyang is a historic name associated with the city of Hefei, the capital of Anhui Province in eastern China.
  • E. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • 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: Anlu
Triple: [Xiaogan, administrativeDivision, Anlu]
Generated description
Anlu is a county-level city in central China's Hubei province, known for its historical significance and agricultural economy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Anlu
Target entity description: Anlu is a county-level city in central China's Hubei province, known for its historical significance and agricultural economy.
  • A. Guanggu
    Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
  • B. Guguan
    Guguan is an uninhabited volcanic island in the Northern Mariana Islands chain in the western Pacific Ocean.
  • C. Jianye
    Jianye is an ancient name for the city now known as Nanjing, a historically significant capital in several Chinese dynasties.
  • D. Luyang
    Luyang is a historic name associated with the city of Hefei, the capital of Anhui Province in eastern China.
  • E. Zhizhong
    Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb026aa7c8190bc988d3ee0fd9f41 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9b4b4f08190a0e5ad50de5c0ba8 completed March 8, 2026, 7:10 p.m.
NEDg Description generation batch_69adcd9359b88190ad312ff0389ff1a6 completed March 8, 2026, 7:27 p.m.
NED2 Entity disambiguation (via description) batch_69adce11558c8190bd8c6341837eb792 completed March 8, 2026, 7:29 p.m.
Created at: March 4, 2026, 7:33 p.m.