Triple

T1695725
Position Surface form Disambiguated ID Type / Status
Subject Shiyan E36652 entity
Predicate hasMunicipalSeat P1474 FINISHED
Object Maojian District
Maojian District is the central urban district and administrative seat of Shiyan, a prefecture-level city in Hubei Province, China.
E217782 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: Maojian District | Statement: [Shiyan, hasMunicipalSeat, Maojian District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maojian District
Context triple: [Shiyan, hasMunicipalSeat, Maojian District]
  • A. Yuhua District
    Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • B. Qingshan District
    Qingshan District is an urban district of Wuhan in Hubei Province, China, known for its heavy industry and riverside location along the Yangtze River.
  • C. Xicheng District
    Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
  • D. Tianxin District
    Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
  • E. Beibei District
    Beibei District is an urban district of Chongqing, China, known for its scenic landscapes, hot springs, and educational institutions.
  • 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: Maojian District
Triple: [Shiyan, hasMunicipalSeat, Maojian District]
Generated description
Maojian District is the central urban district and administrative seat of Shiyan, a prefecture-level city in Hubei Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maojian District
Target entity description: Maojian District is the central urban district and administrative seat of Shiyan, a prefecture-level city in Hubei Province, China.
  • A. Yuhua District
    Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • B. Qingshan District
    Qingshan District is an urban district of Wuhan in Hubei Province, China, known for its heavy industry and riverside location along the Yangtze River.
  • C. Xicheng District
    Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
  • D. Tianxin District
    Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
  • E. Beibei District
    Beibei District is an urban district of Chongqing, China, known for its scenic landscapes, hot springs, and educational institutions.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b645a081909dafdf7a32f2a389 completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3b9a2f4819082ca2e9f838f7b9e completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf79bddf48190909bdcee31b55379 completed March 8, 2026, 10:26 p.m.
NED2 Entity disambiguation (via description) batch_69adf8153e5881908acc441f68623890 completed March 8, 2026, 10:28 p.m.
Created at: March 4, 2026, 7:30 p.m.