Triple

T1595918
Position Surface form Disambiguated ID Type / Status
Subject Shiga E34281 entity
Predicate hasCity P316 FINISHED
Object Ryūō
Ryūō is a town in Shiga Prefecture, Japan, known for its location near Lake Biwa and its blend of rural landscapes with growing commercial development.
 E265182 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: Ryūō | Statement: [Shiga, hasCity, Ryūō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ryūō
Context triple: [Shiga, hasCity, Ryūō]
  • A. Shintaro
    Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
  • B. Akinobu
    Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
  • C. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • D. Masahito
    Masahito is the personal name of Prince Hitachi, a member of the Japanese imperial family and younger brother of Emperor Emeritus Akihito.
  • E. Yasuhiro
    Yasuhiro is a Japanese masculine given name borne by various notable figures in politics, sports, and entertainment.
  • 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: Ryūō
Triple: [Shiga, hasCity, Ryūō]
Generated description
Ryūō is a town in Shiga Prefecture, Japan, known for its location near Lake Biwa and its blend of rural landscapes with growing commercial development.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ryūō
Target entity description: Ryūō is a town in Shiga Prefecture, Japan, known for its location near Lake Biwa and its blend of rural landscapes with growing commercial development.
  • A. Shintaro
    Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
  • B. Akinobu
    Akinobu is a Japanese masculine given name that can be written with various kanji combinations and is borne by several notable individuals.
  • C. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • D. Masahito
    Masahito is the personal name of Prince Hitachi, a member of the Japanese imperial family and younger brother of Emperor Emeritus Akihito.
  • E. Yasuhiro
    Yasuhiro is a Japanese masculine given name borne by various notable figures in politics, sports, and entertainment.
  • 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_69a885fdcb9c819081ce6f0b8cd477dd completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9092ccb388190b2f3ed86b3853651 completed March 5, 2026, 4:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebef5ac7c81908015969c04fcc425 completed March 9, 2026, 12:37 p.m.
NEDg Description generation batch_69aec38a3b8081909f6a8474e59f7575 completed March 9, 2026, 12:56 p.m.
NED2 Entity disambiguation (via description) batch_69aec3e8aa9c8190b9930f1af57b8380 completed March 9, 2026, 12:58 p.m.
Created at: March 4, 2026, 7:27 p.m.