Triple

T7401674
Position Surface form Disambiguated ID Type / Status
Subject Lake Biwa E170762 entity
Predicate hasCityOnShore P969 FINISHED
Object Otsu
Otsu is the capital city of Shiga Prefecture in Japan, known as a historic transportation hub near Kyoto and for its scenic lakeside setting and cultural sites.
 E167718 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: Otsu | Statement: [Lake Biwa, hasCityOnShore, Otsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Otsu
Context triple: [Lake Biwa, hasCityOnShore, Otsu]
  • A. Shuji
    Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
  • B. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • C. Yamazoe
    Yamazoe is a rural village in Nara Prefecture, Japan, known for its mountainous terrain, forests, and traditional countryside landscapes.
  • D. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • E. Sumio
    Sumio is a Japanese physicist best known for his pioneering discovery and characterization of carbon nanotubes.
  • 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: Otsu
Triple: [Lake Biwa, hasCityOnShore, Otsu]
Generated description
Otsu is the capital city of Shiga Prefecture in Japan, known as a historic transportation hub near Kyoto and for its scenic lakeside setting and cultural sites.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Otsu
Target entity description: Otsu is the capital city of Shiga Prefecture in Japan, known as a historic transportation hub near Kyoto and for its scenic lakeside setting and cultural sites.
  • A. Otsu chosen
    Otsu is the capital city of Shiga Prefecture in Japan, known for its location on the southwestern shore of Lake Biwa and its historic temples and lakeside scenery.
  • B. Shuji
    Shuji is a Japanese given name most notably borne by Nobel Prize–winning physicist Shuji Nakamura.
  • C. Takaichi
    Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
  • D. Yamazoe
    Yamazoe is a rural village in Nara Prefecture, Japan, known for its mountainous terrain, forests, and traditional countryside landscapes.
  • E. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • F. None of above.

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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f26d6d6081909c7272a9ccae0d97 completed March 27, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81110d7648190a8938db7061be454 completed March 28, 2026, 5:34 p.m.
NEDg Description generation batch_69c812b0b534819095dd2ae63ca7b2d0 completed March 28, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_69c8147b3f3c8190ada85c9e37bf5e2b completed March 28, 2026, 5:48 p.m.
Created at: March 27, 2026, 3:10 p.m.