Triple

T15855528
Position Surface form Disambiguated ID Type / Status
Subject Ōtsu E384443 entity
Predicate nativeName P15 FINISHED
Object 大津市
大津市 is the capital city of Shiga Prefecture in Japan, located on the southwestern shore of Lake Biwa and known for its historic temples and scenic waterfront.
E1179527 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: 大津市 | Statement: [Ōtsu, nativeName, 大津市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 大津市
Context triple: [Ōtsu, nativeName, 大津市]
  • A. 川越市
    川越市 is a historic city in Saitama Prefecture, Japan, famed for its well-preserved Edo-period streetscapes and traditional warehouse-style buildings that have earned it the nickname "Little Edo."
  • B. 大東市
    大東市は大阪府北河内地域に位置し、住宅地と工業地帯が混在する中核的な都市です。
  • C. 丹波市
    丹波市 is a rural city in central Hyōgo Prefecture, Japan, known for its historic castle town atmosphere, agricultural products, and scenic natural landscapes.
  • D. 木津川市
    木津川市は、京都府南部に位置し、奈良県に隣接する住宅都市・歴史観光地として発展している市です。
  • E. 津山市
    津山市 is a historic castle town and regional city in Okayama Prefecture, Japan, known for Tsuyama Castle ruins and its preserved traditional streetscapes.
  • 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: 大津市
Triple: [Ōtsu, nativeName, 大津市]
Generated description
大津市 is the capital city of Shiga Prefecture in Japan, located on the southwestern shore of Lake Biwa and known for its historic temples and scenic waterfront.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 大津市
Target entity description: 大津市 is the capital city of Shiga Prefecture in Japan, located on the southwestern shore of Lake Biwa and known for its historic temples and scenic waterfront.
  • A. 川越市
    川越市 is a historic city in Saitama Prefecture, Japan, famed for its well-preserved Edo-period streetscapes and traditional warehouse-style buildings that have earned it the nickname "Little Edo."
  • B. 大東市
    大東市は大阪府北河内地域に位置し、住宅地と工業地帯が混在する中核的な都市です。
  • C. 丹波市
    丹波市 is a rural city in central Hyōgo Prefecture, Japan, known for its historic castle town atmosphere, agricultural products, and scenic natural landscapes.
  • D. 木津川市
    木津川市は、京都府南部に位置し、奈良県に隣接する住宅都市・歴史観光地として発展している市です。
  • E. 津山市
    津山市 is a historic castle town and regional city in Okayama Prefecture, Japan, known for Tsuyama Castle ruins and its preserved traditional streetscapes.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e14caf6ae481909ae1385cb4548612 completed April 16, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa14977408190815ef02cc54075cc completed May 9, 2026, 9:04 p.m.
NEDg Description generation batch_69ffa41a86ec8190b46d541965ecf26e completed May 9, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69ffa496f3e48190b8dc82bece548aec completed May 9, 2026, 9:18 p.m.
Created at: April 10, 2026, 4:50 a.m.