Triple

T15347513
Position Surface form Disambiguated ID Type / Status
Subject Benxi E366961 entity
Predicate hasSubdivision P747 FINISHED
Object Mingshan District
Mingshan District is an urban administrative district of the city of Benxi in Liaoning Province, northeastern China.
E1244123 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: Mingshan District | Statement: [Benxi, hasSubdivision, Mingshan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mingshan District
Context triple: [Benxi, hasSubdivision, Mingshan District]
  • A. Yuanbaoshan District
    Yuanbaoshan District is an urban administrative district within the city of Chifeng in Inner Mongolia, China.
  • B. Fengnan District
    Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
  • C. Shunqing District
    Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
  • D. Jiancaoping District
    Jiancaoping District is an urban district of Taiyuan, the capital city of Shanxi Province in northern China, known for its industrial development and residential areas.
  • E. Yicheng District
    Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
  • 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: Mingshan District
Triple: [Benxi, hasSubdivision, Mingshan District]
Generated description
Mingshan District is an urban administrative district of the city of Benxi in Liaoning Province, northeastern China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mingshan District
Target entity description: Mingshan District is an urban administrative district of the city of Benxi in Liaoning Province, northeastern China.
  • A. Yuanbaoshan District
    Yuanbaoshan District is an urban administrative district within the city of Chifeng in Inner Mongolia, China.
  • B. Fengnan District
    Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
  • C. Shunqing District
    Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
  • D. Jiancaoping District
    Jiancaoping District is an urban district of Taiyuan, the capital city of Shanxi Province in northern China, known for its industrial development and residential areas.
  • E. Yicheng District
    Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e1749bc8190a8b9cbcb27288a5b completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbf2567c81909ab6054ade27afac completed May 10, 2026, 7:26 p.m.
NEDg Description generation batch_6a0114d33cac819083d8e542ea5bc274 completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0115c583608190bf07ac205399f253 completed May 10, 2026, 11:33 p.m.
Created at: April 10, 2026, 3:17 a.m.