Triple

T14002412
Position Surface form Disambiguated ID Type / Status
Subject Changzhi E336861 entity
Predicate hasChineseName P4878 FINISHED
Object 长治市
长治市是位于中国山西省东南部的一座地级市，以其悠久历史、红色革命文化和煤炭等资源型工业而闻名。
 E1072970 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: 长治市 | Statement: [Changzhi, hasChineseName, 长治市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 长治市
Context triple: [Changzhi, hasChineseName, 长治市]
  • A. Wolverhampton
    Wolverhampton is a large industrial city in England’s West Midlands, known historically for its role in the coal, steel, and manufacturing industries.
  • B. Coventry
    Coventry is a town in central Rhode Island known for its suburban communities, historic villages, and extensive outdoor recreation areas.
  • C. Coventry
    Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
  • D. Swindon
    Swindon is a large town in Wiltshire, England, known as a major commercial and commuter hub in the southwest with strong railway and industrial heritage.
  • E. Telford
    Telford is a given name most notably associated with Telford Taylor, the American lawyer and chief prosecutor at the Nuremberg Trials.
  • 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: 长治市
Triple: [Changzhi, hasChineseName, 长治市]
Generated description
长治市是位于中国山西省东南部的一座地级市，以其悠久历史、红色革命文化和煤炭等资源型工业而闻名。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 长治市
Target entity description: 长治市是位于中国山西省东南部的一座地级市，以其悠久历史、红色革命文化和煤炭等资源型工业而闻名。
  • A. Wolverhampton
    Wolverhampton is a large industrial city in England’s West Midlands, known historically for its role in the coal, steel, and manufacturing industries.
  • B. Coventry
    Coventry is a town in central Rhode Island known for its suburban communities, historic villages, and extensive outdoor recreation areas.
  • C. Coventry
    Coventry is a historic city in England, best known for its medieval cathedral destroyed in World War II and its symbolic postwar reconciliation efforts.
  • D. Swindon
    Swindon is a large town in Wiltshire, England, known as a major commercial and commuter hub in the southwest with strong railway and industrial heritage.
  • E. Telford
    Telford is a given name most notably associated with Telford Taylor, the American lawyer and chief prosecutor at the Nuremberg Trials.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed06a50819093ddc64f55050689 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbaca180988190bbfc93bd708688d6 completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbae8f83f481909ac16d4bb66ea79d completed May 6, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_69fbaf71ad648190b9128851ba62590e completed May 6, 2026, 9:15 p.m.
Created at: April 9, 2026, 10:19 p.m.