Triple

T262017
Position Surface form Disambiguated ID Type / Status
Subject Tokyo E5560 entity
Predicate formerName P65 FINISHED
Object Edo
Edo was the historical name of Japan’s capital during the Tokugawa shogunate, a major political and cultural center that later became modern Tokyo.
 E69445 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: Edo | Statement: [Tokyo, formerName, Edo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Edo
Context triple: [Tokyo, formerName, Edo]
  • A. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • 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. Nara
    Nara is an ancient Japanese city renowned for its early role as a national capital, its historic temples, and its culturally significant deer-filled parks.
  • E. Minoh
    Minoh is a suburban city in northern Osaka Prefecture, Japan, known for its scenic Minoh Waterfall, autumn foliage, and residential communities.
  • 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: Edo
Triple: [Tokyo, formerName, Edo]
Generated description
Edo was the historical name of Japan’s capital during the Tokugawa shogunate, a major political and cultural center that later became modern Tokyo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Edo
Target entity description: Edo was the historical name of Japan’s capital during the Tokugawa shogunate, a major political and cultural center that later became modern Tokyo.
  • A. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • 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. Nara
    Nara is an ancient Japanese city renowned for its early role as a national capital, its historic temples, and its culturally significant deer-filled parks.
  • E. Minoh
    Minoh is a suburban city in northern Osaka Prefecture, Japan, known for its scenic Minoh Waterfall, autumn foliage, and residential communities.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d7428dc8190ae12b12a21fcc6cb completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a4e3f024b48190b7c16820d5cee198 completed March 2, 2026, 1:12 a.m.
NEDg Description generation batch_69a4e48a2d0081908aea3bcc51daabf2 completed March 2, 2026, 1:14 a.m.
NED2 Entity disambiguation (via description) batch_69a4e514d1e88190adfb8093e328801a completed March 2, 2026, 1:17 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.