Triple

T15499646
Position Surface form Disambiguated ID Type / Status
Subject Shaoguan E378915 entity
Predicate hasCountyLevelCity P27799 FINISHED
Object Lechang
Lechang is a county-level city administered by Shaoguan in northern Guangdong Province, China, known for its mountainous terrain and role as a regional transport and commercial hub.
E1161628 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: Lechang | Statement: [Shaoguan, hasCountyLevelCity, Lechang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lechang
Context triple: [Shaoguan, hasCountyLevelCity, Lechang]
  • A. Longchang
    Longchang was a Chinese era name used during the Northern Qi dynasty to designate a specific reign period.
  • B. Changling
    Changling is the largest and best-preserved mausoleum within Beijing’s Ming Tombs complex, built for the Yongle Emperor and his empress.
  • C. Changle
    Changle is a coastal city in eastern China located on the Shandong Peninsula.
  • D. Shancheng
    Shancheng is a Chinese nickname meaning "Mountain City," commonly used to refer to the city of Chongqing, known for its steep terrain and hilly urban landscape.
  • E. Chardzhou
    Chardzhou is the former name of Turkmenabat, a major city in eastern Turkmenistan located on the Amu Darya River.
  • 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: Lechang
Triple: [Shaoguan, hasCountyLevelCity, Lechang]
Generated description
Lechang is a county-level city administered by Shaoguan in northern Guangdong Province, China, known for its mountainous terrain and role as a regional transport and commercial hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lechang
Target entity description: Lechang is a county-level city administered by Shaoguan in northern Guangdong Province, China, known for its mountainous terrain and role as a regional transport and commercial hub.
  • A. Longchang
    Longchang was a Chinese era name used during the Northern Qi dynasty to designate a specific reign period.
  • B. Changling
    Changling is the largest and best-preserved mausoleum within Beijing’s Ming Tombs complex, built for the Yongle Emperor and his empress.
  • C. Changle
    Changle is a coastal city in eastern China located on the Shandong Peninsula.
  • D. Shancheng
    Shancheng is a Chinese nickname meaning "Mountain City," commonly used to refer to the city of Chongqing, known for its steep terrain and hilly urban landscape.
  • E. Chardzhou
    Chardzhou is the former name of Turkmenabat, a major city in eastern Turkmenistan located on the Amu Darya River.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fcb4e8c81908e4ab463e3ae252b completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d4a9bf88190b7c6b4874abe165f completed May 9, 2026, 1:57 p.m.
NEDg Description generation batch_69ff3e77330881909f13327aa2616203 completed May 9, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_69ff3eed56b881908363380284e9d81b completed May 9, 2026, 2:04 p.m.
Created at: April 10, 2026, 3:54 a.m.