Triple

T16887353
Position Surface form Disambiguated ID Type / Status
Subject Masaoka Shiki E421573 entity
Predicate pseudonym P39 FINISHED
Object Shiki
Shiki was the pen name of Masaoka Shiki, a pioneering Meiji-era Japanese poet and critic who modernized haiku and tanka.
 E1238625 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: Shiki | Statement: [Masaoka Shiki, pseudonym, Shiki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shiki
Context triple: [Masaoka Shiki, pseudonym, Shiki]
  • A. Shiki
    Shiki is a city in Saitama Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
  • B. Shikinaisha
    Shikinaisha are Shinto shrines listed in the ancient Engishiki regulations, regarded as especially important regional sanctuaries in Japan.
  • C. Aishō
    Aishō is a town in Shiga Prefecture, Japan, known for its rural character and historical sites.
  • D. Nishikatsura
    Nishikatsura is a small town in Yamanashi Prefecture, Japan, known for its scenic views of Mount Fuji and traditional textile industry.
  • E. Shinsekai
    Shinsekai is a retro entertainment district in Osaka, Japan, known for its nostalgic Showa-era atmosphere, street food, and neon-lit nightlife.
  • 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: Shiki
Triple: [Masaoka Shiki, pseudonym, Shiki]
Generated description
Shiki was the pen name of Masaoka Shiki, a pioneering Meiji-era Japanese poet and critic who modernized haiku and tanka.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shiki
Target entity description: Shiki was the pen name of Masaoka Shiki, a pioneering Meiji-era Japanese poet and critic who modernized haiku and tanka.
  • A. Shiki
    Shiki is a city in Saitama Prefecture, Japan, known as a residential and commercial hub within the Greater Tokyo metropolitan area.
  • B. Shikinaisha
    Shikinaisha are Shinto shrines listed in the ancient Engishiki regulations, regarded as especially important regional sanctuaries in Japan.
  • C. Aishō
    Aishō is a town in Shiga Prefecture, Japan, known for its rural character and historical sites.
  • D. Nishikatsura
    Nishikatsura is a small town in Yamanashi Prefecture, Japan, known for its scenic views of Mount Fuji and traditional textile industry.
  • E. Shinsekai
    Shinsekai is a retro entertainment district in Osaka, Japan, known for its nostalgic Showa-era atmosphere, street food, and neon-lit nightlife.
  • 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc1f42481909dcf595358c23497 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2befaa88190ba83dc17aa66b541 completed May 10, 2026, 5:39 p.m.
NEDg Description generation batch_6a00c392b4488190bcfcb40351821f92 completed May 10, 2026, 5:42 p.m.
NED2 Entity disambiguation (via description) batch_6a00c44e37b48190a62b315ddbbd4ec4 completed May 10, 2026, 5:45 p.m.
Created at: April 10, 2026, 5:29 a.m.