Triple

T7385091
Position Surface form Disambiguated ID Type / Status
Subject Zoomlion E170359 entity
Predicate competitor P1375 FINISHED
Object LiuGong
LiuGong is a major Chinese construction machinery manufacturer known for its wheel loaders, excavators, and other heavy equipment sold worldwide.
 E660782 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: LiuGong | Statement: [Zoomlion, competitor, LiuGong]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LiuGong
Context triple: [Zoomlion, competitor, LiuGong]
  • A. Liulichang
    Liulichang is a famous historic cultural street in Beijing known for its traditional architecture, antique shops, and stores selling calligraphy, paintings, and rare books.
  • B. Liu
    Liu is a common Chinese surname borne by numerous historical figures, political leaders, and cultural personalities across Chinese history.
  • C. Liang
    Liang is a common Chinese surname borne by numerous historical figures, scholars, and public personalities across the Chinese-speaking world.
  • D. Liu Jian
    Liu Jian was a prominent Ming dynasty statesman and grand secretary who played a key role in government during the reign of the Hongzhi Emperor.
  • E. Zhihong
    Zhihong is a Chinese given name that represents an alternative romanization of the name Zhizhong.
  • 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: LiuGong
Triple: [Zoomlion, competitor, LiuGong]
Generated description
LiuGong is a major Chinese construction machinery manufacturer known for its wheel loaders, excavators, and other heavy equipment sold worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LiuGong
Target entity description: LiuGong is a major Chinese construction machinery manufacturer known for its wheel loaders, excavators, and other heavy equipment sold worldwide.
  • A. Liulichang
    Liulichang is a famous historic cultural street in Beijing known for its traditional architecture, antique shops, and stores selling calligraphy, paintings, and rare books.
  • B. Liu
    Liu is a common Chinese surname borne by numerous historical figures, political leaders, and cultural personalities across Chinese history.
  • C. Liang
    Liang is a common Chinese surname borne by numerous historical figures, scholars, and public personalities across the Chinese-speaking world.
  • D. Liu Jian
    Liu Jian was a prominent Ming dynasty statesman and grand secretary who played a key role in government during the reign of the Hongzhi Emperor.
  • E. Zhihong
    Zhihong is a Chinese given name that represents an alternative romanization of the name Zhizhong.
  • 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_69c68a5d0ed08190b6d361e68f813330 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1efe1308190b96eefbff56140be completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802e23714819094a1b31c82a27fee completed March 28, 2026, 4:33 p.m.
NEDg Description generation batch_69c8038127408190947cb7002ccc0dec completed March 28, 2026, 4:36 p.m.
NED2 Entity disambiguation (via description) batch_69c8040a40088190b37192429678fd3e completed March 28, 2026, 4:38 p.m.
Created at: March 27, 2026, 3:08 p.m.