Triple

T105779
Position Surface form Disambiguated ID Type / Status
Subject Japan Standard Time E2133 entity
Predicate usedByRegion P908 FINISHED
Object Sapporo
Sapporo is the capital and largest city of Japan’s northern Hokkaido prefecture, known for its annual snow festival, beer, and ski resorts.
 E40366 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: Sapporo | Statement: [Japan Standard Time, usedByRegion, Sapporo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sapporo
Context triple: [Japan Standard Time, usedByRegion, Sapporo]
  • A. Niigata
    Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
  • B. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • C. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • D. Kyoto
    Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
  • E. Fukuoka
    Fukuoka is a major Japanese city on the northern shore of Kyushu, known as an important economic, cultural, and transportation hub with a busy international port.
  • 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: Sapporo
Triple: [Japan Standard Time, usedByRegion, Sapporo]
Generated description
Sapporo is the capital and largest city of Japan’s northern Hokkaido prefecture, known for its annual snow festival, beer, and ski resorts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sapporo
Target entity description: Sapporo is the capital and largest city of Japan’s northern Hokkaido prefecture, known for its annual snow festival, beer, and ski resorts.
  • A. Niigata
    Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
  • B. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • C. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • D. Kyoto
    Kyoto is a historic Japanese city renowned for its well-preserved temples, traditional wooden houses, and role as the former imperial capital.
  • E. Fukuoka
    Fukuoka is a major Japanese city on the northern shore of Kyushu, known as an important economic, cultural, and transportation hub with a busy international port.
  • 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_69a24e0a5b7c81908d52da08c60dabc4 completed Feb. 28, 2026, 2:08 a.m.
NER Named-entity recognition batch_69a25b7e2c188190b1dd8aafd4507a99 completed Feb. 28, 2026, 3:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3bc1de7408190833fe3fb65c2a7b3 completed March 1, 2026, 4:10 a.m.
NEDg Description generation batch_69a3c007e0148190b41b900e59c4bbdb completed March 1, 2026, 4:26 a.m.
NED2 Entity disambiguation (via description) batch_69a3c18c7a188190bde3478b27ba8193 completed March 1, 2026, 4:33 a.m.
Created at: Feb. 28, 2026, 2:12 a.m.