Triple

T4470887
Position Surface form Disambiguated ID Type / Status
Subject Hugo von Hofmannsthal E98492 entity
Predicate movement P81 FINISHED
Object Jung-Wien
Jung-Wien was a late 19th-century Viennese literary circle of young modernist writers and critics, including figures like Hugo von Hofmannsthal, that helped shape Austrian literature and culture.
 E441125 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: Jung-Wien | Statement: [Hugo von Hofmannsthal, movement, Jung-Wien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jung-Wien
Context triple: [Hugo von Hofmannsthal, movement, Jung-Wien]
  • A. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • B. Jang
    Jang is one of the small islands that make up Maloelap Atoll in the Republic of the Marshall Islands.
  • C. Gwan-eum
    Gwan-eum is the Korean name for Guanyin, the bodhisattva of compassion widely revered in East Asian Buddhism.
  • D. Jin
    Jin is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into Chinese society while preserving distinct communal identities.
  • E. Jin
    Jin is the standard abbreviation used to refer to Shanxi Province in 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: Jung-Wien
Triple: [Hugo von Hofmannsthal, movement, Jung-Wien]
Generated description
Jung-Wien was a late 19th-century Viennese literary circle of young modernist writers and critics, including figures like Hugo von Hofmannsthal, that helped shape Austrian literature and culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jung-Wien
Target entity description: Jung-Wien was a late 19th-century Viennese literary circle of young modernist writers and critics, including figures like Hugo von Hofmannsthal, that helped shape Austrian literature and culture.
  • A. Kwang-chou
    Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
  • B. Jang
    Jang is one of the small islands that make up Maloelap Atoll in the Republic of the Marshall Islands.
  • C. Gwan-eum
    Gwan-eum is the Korean name for Guanyin, the bodhisattva of compassion widely revered in East Asian Buddhism.
  • D. Jin
    Jin is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into Chinese society while preserving distinct communal identities.
  • E. Jin
    Jin is the standard abbreviation used to refer to Shanxi Province in 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_69b3454b4ae481908967426dd37284d6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b356b6a1f48190a39f5411648c40ff completed March 13, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6286c75b08190bd683d300f6c97f0 completed March 15, 2026, 3:33 a.m.
NEDg Description generation batch_69b6295627848190a7bb6b8943b0e3f1 completed March 15, 2026, 3:36 a.m.
NED2 Entity disambiguation (via description) batch_69b629be765c81908c1f6ccfc75604d1 completed March 15, 2026, 3:38 a.m.
Created at: March 12, 2026, 11:35 p.m.