Triple

T12445064
Position Surface form Disambiguated ID Type / Status
Subject Nichiren E297376 entity
Predicate teacherOf P48 FINISHED
Object Nitchō
Nitchō was a prominent early disciple and priest of the Japanese Buddhist reformer Nichiren, helping to spread and institutionalize Nichiren Buddhism in the 13th century.
 E991371 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: Nitchō | Statement: [Nichiren, teacherOf, Nitchō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nitchō
Context triple: [Nichiren, teacherOf, Nitchō]
  • A. Kiyosu
    Kiyosu is a city in central Japan known historically for Kiyosu Castle and its role as a political center during the Sengoku period.
  • B. Bunkyū
    Bunkyū was a Japanese era name of the late Edo period, spanning the early 1860s during the reign of Emperor Kōmei and marked by growing internal unrest and foreign pressure on Japan.
  • C. Tadaoka
    Tadaoka is a small coastal town in Osaka Prefecture, Japan, known for being one of the smallest municipalities in the country by area.
  • D. Enyō
    Enyō is a minor Greek goddess associated with war, destruction, and the bloody chaos of battle, often depicted as a companion of Ares.
  • E. Ansei
    Ansei was a Japanese era in the mid-19th century marked by political unrest, foreign pressure to open Japan, and significant natural disasters.
  • 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: Nitchō
Triple: [Nichiren, teacherOf, Nitchō]
Generated description
Nitchō was a prominent early disciple and priest of the Japanese Buddhist reformer Nichiren, helping to spread and institutionalize Nichiren Buddhism in the 13th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nitchō
Target entity description: Nitchō was a prominent early disciple and priest of the Japanese Buddhist reformer Nichiren, helping to spread and institutionalize Nichiren Buddhism in the 13th century.
  • A. Kiyosu
    Kiyosu is a city in central Japan known historically for Kiyosu Castle and its role as a political center during the Sengoku period.
  • B. Bunkyū
    Bunkyū was a Japanese era name of the late Edo period, spanning the early 1860s during the reign of Emperor Kōmei and marked by growing internal unrest and foreign pressure on Japan.
  • C. Tadaoka
    Tadaoka is a small coastal town in Osaka Prefecture, Japan, known for being one of the smallest municipalities in the country by area.
  • D. Enyō
    Enyō is a minor Greek goddess associated with war, destruction, and the bloody chaos of battle, often depicted as a companion of Ares.
  • E. Ansei
    Ansei was a Japanese era in the mid-19th century marked by political unrest, foreign pressure to open Japan, and significant natural disasters.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8fd9848190a83410353d88ea8d completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6556839908190ac0401d373ad0fa9 completed May 2, 2026, 7:50 p.m.
NEDg Description generation batch_69f656a6dafc81908acf59c0ba65189a completed May 2, 2026, 7:55 p.m.
NED2 Entity disambiguation (via description) batch_69f65b4d109c8190b48c71f664e7bb3f completed May 2, 2026, 8:15 p.m.
Created at: April 8, 2026, 9:55 p.m.