Triple

T490152
Position Surface form Disambiguated ID Type / Status
Subject Ulm E9969 entity
Predicate twinCity P1072 FINISHED
Object Jinzhou
Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
 E77141 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: Jinzhou | Statement: [Ulm, twinCity, Jinzhou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jinzhou
Context triple: [Ulm, twinCity, Jinzhou]
  • A. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • B. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • C. Xiaogan
    Xiaogan is a prefecture-level city in central China known for its cultural heritage and proximity to the provincial capital, Wuhan, within Hubei Province.
  • D. Huangshi
    Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
  • E. Xiangyang
    Xiangyang is a historic prefecture-level city in northern Hubei Province, China, known for its strategic location on the Han River and well-preserved ancient city walls.
  • 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: Jinzhou
Triple: [Ulm, twinCity, Jinzhou]
Generated description
Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jinzhou
Target entity description: Jinzhou is a prefecture-level port city in southwestern Liaoning Province, northeastern China, known for its industrial base and coastal location on the Bohai Sea.
  • A. Shenyang
    Shenyang is a major industrial and historical city in northeastern China and the capital of Liaoning Province.
  • B. Tianjin
    Tianjin is a major port city and industrial hub in northern China, located near Beijing along the Bohai Sea.
  • C. Xiaogan
    Xiaogan is a prefecture-level city in central China known for its cultural heritage and proximity to the provincial capital, Wuhan, within Hubei Province.
  • D. Huangshi
    Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
  • E. Xiangyang
    Xiangyang is a historic prefecture-level city in northern Hubei Province, China, known for its strategic location on the Han River and well-preserved ancient city walls.
  • 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_69a2e802e2908190ab17c9479e0b6412 completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f0e22a308190b04d12974fd08a38 completed Feb. 28, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a55544eda481908fae6a9f77ff9d97 completed March 2, 2026, 9:15 a.m.
NEDg Description generation batch_69a5595a7fac8190944a6b6146623673 completed March 2, 2026, 9:33 a.m.
NED2 Entity disambiguation (via description) batch_69a559ca6c6881908451d3b024745277 completed March 2, 2026, 9:35 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.