Triple

T20974850
Position Surface form Disambiguated ID Type / Status
Subject Katayama Tōkuma E516597 entity
Predicate familyName P18 FINISHED
Object Katayama
Katayama is a Japanese surname borne by various notable figures in fields such as politics, architecture, and sports.
 E1541178 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: Katayama | Statement: [Katayama Tōkuma, familyName, Katayama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Katayama
Context triple: [Katayama Tōkuma, familyName, Katayama]
  • A. Ōyama
    Ōyama is a Japanese surname borne by various notable figures in Japan’s military, political, and cultural history.
  • B. Oyama
    Oyama is a city in Tochigi Prefecture, Japan, known as a key commercial and transportation hub within the northern Kantō region.
  • C. Oyama
    Oyama is a small genus of flowering plants in the magnolia family, known for its ornamental, magnolia-like shrubs or small trees.
  • D. Yagiyama
    Yagiyama is a hilly district in Sendai, Japan, known for its zoo, amusement park, and scenic views over the city.
  • E. Maihara
    Maihara was a former town in Shiga Prefecture, Japan, that later became part of the city of Maibara through a municipal merger.
  • 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: Katayama
Triple: [Katayama Tōkuma, familyName, Katayama]
Generated description
Katayama is a Japanese surname borne by various notable figures in fields such as politics, architecture, and sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Katayama
Target entity description: Katayama is a Japanese surname borne by various notable figures in fields such as politics, architecture, and sports.
  • A. Ōyama
    Ōyama is a Japanese surname borne by various notable figures in Japan’s military, political, and cultural history.
  • B. Oyama
    Oyama is a city in Tochigi Prefecture, Japan, known as a key commercial and transportation hub within the northern Kantō region.
  • C. Oyama
    Oyama is a small genus of flowering plants in the magnolia family, known for its ornamental, magnolia-like shrubs or small trees.
  • D. Yagiyama
    Yagiyama is a hilly district in Sendai, Japan, known for its zoo, amusement park, and scenic views over the city.
  • E. Maihara
    Maihara was a former town in Shiga Prefecture, Japan, that later became part of the city of Maibara through a municipal merger.
  • 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_69e0b4fee5ac8190875fa9ceba1a5e5e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fba307d88190b728544d1b6d0bb6 completed April 21, 2026, 4:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b1dbd34e88190a0416e29251a3311 completed May 18, 2026, 2:10 p.m.
NEDg Description generation batch_6a0b1e511d548190934ed8e1df7441de completed May 18, 2026, 2:12 p.m.
NED2 Entity disambiguation (via description) batch_6a0b1f1e599481908a91e86f58402522 completed May 18, 2026, 2:15 p.m.
Created at: April 16, 2026, 1:46 p.m.