Triple

T4825730
Position Surface form Disambiguated ID Type / Status
Subject Suzhou E107819 entity
Predicate hasWaterTown P59883 FINISHED
Object Tongli
Tongli is an ancient canal town near Suzhou in China, renowned for its well-preserved stone bridges, traditional architecture, and network of waterways.
E316678 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: Tongli | Statement: [Suzhou, hasWaterTown, Tongli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tongli
Context triple: [Suzhou, hasWaterTown, Tongli]
  • A. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • B. Jinqiao
    Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
  • C. Liyang
    Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
  • D. Xitang
    Xitang is an ancient water town in eastern China renowned for its well-preserved canals, stone bridges, and traditional architecture.
  • E. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • 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: Tongli
Triple: [Suzhou, hasWaterTown, Tongli]
Generated description
Tongli is an ancient canal town near Suzhou in China, renowned for its well-preserved stone bridges, traditional architecture, and network of waterways.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tongli
Target entity description: Tongli is an ancient canal town near Suzhou in China, renowned for its well-preserved stone bridges, traditional architecture, and network of waterways.
  • A. Xiantao
    Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
  • B. Jinqiao
    Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
  • C. Liyang
    Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
  • D. Xitang chosen
    Xitang is an ancient water town in eastern China renowned for its well-preserved canals, stone bridges, and traditional architecture.
  • E. Tongling
    Tongling is a prefecture-level city in eastern China known for its rich copper resources and mining industry.
  • F. None of above.

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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7162427c81908a67a07545f698ae completed March 20, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89d3358c8190bb85ec1835a9f095 completed March 21, 2026, 12:06 p.m.
NEDg Description generation batch_69be8b15879881908ec5ee997daca3cb completed March 21, 2026, 12:12 p.m.
NED2 Entity disambiguation (via description) batch_69be8bc2fc088190a13995f9230adea2 completed March 21, 2026, 12:14 p.m.
Created at: March 20, 2026, 1:24 p.m.