Triple

T8202358
Position Surface form Disambiguated ID Type / Status
Subject 十堰 E191607 entity
Predicate tourismRole P1769 FINISHED
Object 武当山旅游集散中心
武当山旅游集散中心是位于湖北省十堰市、为前往武当山景区游客提供集散换乘、咨询服务和综合配套设施的旅游服务枢纽。
 E718706 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: 武当山旅游集散中心 | Statement: [十堰, tourismRole, 武当山旅游集散中心]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 武当山旅游集散中心
Context triple: [十堰, tourismRole, 武当山旅游集散中心]
  • A. 十堰
    十堰 is a prefecture-level city in northwestern Hubei Province, China, known as an important automotive manufacturing base and gateway to the Wudang Mountains.
  • B. 归元禅寺
    归元禅寺是一座位于湖北省武汉市汉阳区、以古朴建筑和众多佛像而闻名的历史悠久佛教寺院。
  • C. Ancient Building Complex in the Wudang Mountains
    The Ancient Building Complex in the Wudang Mountains is a UNESCO-listed ensemble of Taoist temples, palaces, and monastic buildings renowned for their Ming dynasty architecture and profound cultural and religious significance in China.
  • D. 排云殿
    排云殿是位于北京颐和园内的一组重要宫殿式建筑群，曾为清代皇室举行庆典和宴会的主要场所之一。
  • E. Wutong Mountain Scenic Area
    Wutong Mountain Scenic Area is a popular natural attraction in Shenzhen known for its lush forested peaks, hiking trails, and panoramic views over the city and coastline.
  • 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: 武当山旅游集散中心
Triple: [十堰, tourismRole, 武当山旅游集散中心]
Generated description
武当山旅游集散中心是位于湖北省十堰市、为前往武当山景区游客提供集散换乘、咨询服务和综合配套设施的旅游服务枢纽。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 武当山旅游集散中心
Target entity description: 武当山旅游集散中心是位于湖北省十堰市、为前往武当山景区游客提供集散换乘、咨询服务和综合配套设施的旅游服务枢纽。
  • A. 十堰
    十堰 is a prefecture-level city in northwestern Hubei Province, China, known as an important automotive manufacturing base and gateway to the Wudang Mountains.
  • B. 归元禅寺
    归元禅寺是一座位于湖北省武汉市汉阳区、以古朴建筑和众多佛像而闻名的历史悠久佛教寺院。
  • C. Ancient Building Complex in the Wudang Mountains
    The Ancient Building Complex in the Wudang Mountains is a UNESCO-listed ensemble of Taoist temples, palaces, and monastic buildings renowned for their Ming dynasty architecture and profound cultural and religious significance in China.
  • D. 排云殿
    排云殿是位于北京颐和园内的一组重要宫殿式建筑群，曾为清代皇室举行庆典和宴会的主要场所之一。
  • E. Wutong Mountain Scenic Area
    Wutong Mountain Scenic Area is a popular natural attraction in Shenzhen known for its lush forested peaks, hiking trails, and panoramic views over the city and coastline.
  • 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_69ca82c7f3e08190857bf1fc63b2a10c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb5df84b108190b4407a72a3500af9 completed March 31, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccedc49ba4819099762f200c4e6577 completed April 1, 2026, 10:04 a.m.
NEDg Description generation batch_69ccf1b818588190936f96d53bf08c2b completed April 1, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_69cd05ac594c819087d23a7318fd7704 completed April 1, 2026, 11:46 a.m.
Created at: March 30, 2026, 5:43 p.m.