Triple

T4658678
Position Surface form Disambiguated ID Type / Status
Subject Ötztal E102473 entity
Predicate contains P35 FINISHED
Object Haiming
Haiming is a municipality in the Tyrolean Alps of western Austria, known for its scenic mountain setting and proximity to popular outdoor recreation areas.
 E462710 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: Haiming | Statement: [Ötztal, contains, Haiming]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Haiming
Context triple: [Ötztal, contains, Haiming]
  • A. Shuheng
    Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
  • B. Yuanhong
    Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
  • C. Hui
    The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
  • D. Luoyi
    Luoyi was an ancient Chinese city that served as a major political and cultural center of the Zhou dynasty.
  • E. Shaoqi
    Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of 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: Haiming
Triple: [Ötztal, contains, Haiming]
Generated description
Haiming is a municipality in the Tyrolean Alps of western Austria, known for its scenic mountain setting and proximity to popular outdoor recreation areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Haiming
Target entity description: Haiming is a municipality in the Tyrolean Alps of western Austria, known for its scenic mountain setting and proximity to popular outdoor recreation areas.
  • A. Shuheng
    Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
  • B. Yuanhong
    Yuanhong is a Chinese given name that appears in the full name of the historical figure Li Yuanhong.
  • C. Hui
    The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
  • D. Luoyi
    Luoyi was an ancient Chinese city that served as a major political and cultural center of the Zhou dynasty.
  • E. Shaoqi
    Shaoqi is the given name of Liu Shaoqi, a prominent Chinese revolutionary leader and former President of the People’s Republic of 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63271a548190bd9662b69a45d9a5 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0378825881908fe3214f60be579e completed March 21, 2026, 2:33 a.m.
NEDg Description generation batch_69be04c5549c819087204ac7e2e0e8ea completed March 21, 2026, 2:39 a.m.
NED2 Entity disambiguation (via description) batch_69be05970dcc8190a86771d09f27d9f2 completed March 21, 2026, 2:42 a.m.
Created at: March 20, 2026, 1:15 p.m.