Triple

T224319
Position Surface form Disambiguated ID Type / Status
Subject Shinto E4281 entity
Predicate hasDeity P5606 FINISHED
Object Tenjin
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
 E33677 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: Tenjin | Statement: [Shinto, hasDeity, Tenjin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tenjin
Context triple: [Shinto, hasDeity, Tenjin]
  • A. Takatsuki
    Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
  • B. Taihoku
    Taihoku was the Japanese colonial-era name for Taipei, which served as the administrative and political center of Taiwan under Japanese rule.
  • C. Daikanyama
    Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
  • D. Matsubara
    Matsubara is a suburban city in Japan’s Kansai region, located within Osaka Prefecture and forming part of the Osaka metropolitan area.
  • E. Sendagaya
    Sendagaya is a neighborhood in Tokyo known for its sports facilities, including the National Stadium, and its proximity to Shinjuku and Harajuku.
  • 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: Tenjin
Triple: [Shinto, hasDeity, Tenjin]
Generated description
Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tenjin
Target entity description: Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
  • A. Takatsuki
    Takatsuki is a city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
  • B. Taihoku
    Taihoku was the Japanese colonial-era name for Taipei, which served as the administrative and political center of Taiwan under Japanese rule.
  • C. Daikanyama
    Daikanyama is a trendy, upscale neighborhood in Tokyo known for its stylish boutiques, cafes, and relaxed, residential atmosphere.
  • D. Matsubara
    Matsubara is a suburban city in Japan’s Kansai region, located within Osaka Prefecture and forming part of the Osaka metropolitan area.
  • E. Sendagaya
    Sendagaya is a neighborhood in Tokyo known for its sports facilities, including the National Stadium, and its proximity to Shinjuku and Harajuku.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c7194fc8190a2d02d446ae3a75e completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3836ea55c81909135f5f061e47da5 completed March 1, 2026, 12:08 a.m.
NEDg Description generation batch_69a38453dee88190a2b88b147cd826e9 completed March 1, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_69a384b1c0f48190be08f3a44778548d completed March 1, 2026, 12:13 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.