Triple

T9316175
Position Surface form Disambiguated ID Type / Status
Subject Hara Takashi E224126 entity
Predicate alsoKnownAs P39 FINISHED
Object Hara Kei
Hara Kei was a Japanese politician and statesman who served as Prime Minister of Japan in the early 20th century and was notable as the first commoner to hold the office.
E791107 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: Hara Kei | Statement: [Hara Takashi, alsoKnownAs, Hara Kei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hara Kei
Context triple: [Hara Takashi, alsoKnownAs, Hara Kei]
  • A. Narihira
    Narihira is a neighborhood in Sumida, Tokyo, known for its residential character and proximity to major landmarks like Tokyo Skytree.
  • B. Kōgō Heika
    Kōgō Heika is the formal Japanese honorific title used to address the reigning Empress of Japan.
  • C. Shōhō
    Shōhō was a Japanese light aircraft carrier of the Imperial Japanese Navy during World War II, notable for being the first Japanese carrier sunk in the war during the Battle of the Coral Sea.
  • D. Shōhō
    Shōhō was a Japanese era name (nengō) of the early Edo period, used for a brief span in the mid-17th century.
  • E. Hara Sankei
    Hara Sankei was a Japanese businessman and art patron best known for creating and developing the historic Sankeien Garden in Yokohama.
  • 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: Hara Kei
Triple: [Hara Takashi, alsoKnownAs, Hara Kei]
Generated description
Hara Kei was a Japanese politician and statesman who served as Prime Minister of Japan in the early 20th century and was notable as the first commoner to hold the office.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hara Kei
Target entity description: Hara Kei was a Japanese politician and statesman who served as Prime Minister of Japan in the early 20th century and was notable as the first commoner to hold the office.
  • A. Narihira
    Narihira is a neighborhood in Sumida, Tokyo, known for its residential character and proximity to major landmarks like Tokyo Skytree.
  • B. Kōgō Heika
    Kōgō Heika is the formal Japanese honorific title used to address the reigning Empress of Japan.
  • C. Shōhō
    Shōhō was a Japanese era name (nengō) of the early Edo period, used for a brief span in the mid-17th century.
  • D. Shōhō
    Shōhō was a Japanese light aircraft carrier of the Imperial Japanese Navy during World War II, notable for being the first Japanese carrier sunk in the war during the Battle of the Coral Sea.
  • E. Hara Sankei
    Hara Sankei was a Japanese businessman and art patron best known for creating and developing the historic Sankeien Garden in Yokohama.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd358846e48190a8aacfab19d88ae7 completed April 1, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c7acba54819086da668f234321de completed April 4, 2026, 8:11 a.m.
NEDg Description generation batch_69d0c8d9caf88190b595fe2fdf925394 completed April 4, 2026, 8:16 a.m.
NED2 Entity disambiguation (via description) batch_69d0caeb3bf8819082afe90dec3364ec completed April 4, 2026, 8:25 a.m.
Created at: March 30, 2026, 7:37 p.m.