Triple

T5152397
Position Surface form Disambiguated ID Type / Status
Subject Etajima E116226 entity
Predicate formedByMerger P6637 FINISHED
Object Nōmi
Nōmi was a former town in Hiroshima Prefecture, Japan, that later became part of the city of Etajima through a municipal merger.
 E498540 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: Nōmi | Statement: [Etajima, formedByMerger, Nōmi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nōmi
Context triple: [Etajima, formedByMerger, Nōmi]
  • A. Nomi
    Nomi is the new 00-agent who succeeds James Bond in the 2021 James Bond film "No Time to Die."
  • B. Nozomi
    Nozomi is the fastest and most premium Shinkansen (bullet train) service operating on Japan’s Tokaido and Sanyo lines, known for its high speed and frequent departures between major cities like Tokyo and Osaka.
  • C. Isami
    Isami was a 14th-century Indian historian and poet best known for his Persian chronicle "Futuh-us-Salatin," which records the political and military history of the Delhi Sultanate, including the Mongol invasions of India.
  • D. Reona
    Reona is the Japanese given name of Nobel Prize–winning physicist Leo Esaki, known for his pioneering work on quantum tunneling and semiconductor devices.
  • E. Mamoru
    Mamoru is a Japanese masculine given name commonly borne by notable figures in politics, arts, 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: Nōmi
Triple: [Etajima, formedByMerger, Nōmi]
Generated description
Nōmi was a former town in Hiroshima Prefecture, Japan, that later became part of the city of Etajima through a municipal merger.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nōmi
Target entity description: Nōmi was a former town in Hiroshima Prefecture, Japan, that later became part of the city of Etajima through a municipal merger.
  • A. Nomi
    Nomi is the new 00-agent who succeeds James Bond in the 2021 James Bond film "No Time to Die."
  • B. Nozomi
    Nozomi is the fastest and most premium Shinkansen (bullet train) service operating on Japan’s Tokaido and Sanyo lines, known for its high speed and frequent departures between major cities like Tokyo and Osaka.
  • C. Isami
    Isami was a 14th-century Indian historian and poet best known for his Persian chronicle "Futuh-us-Salatin," which records the political and military history of the Delhi Sultanate, including the Mongol invasions of India.
  • D. Reona
    Reona is the Japanese given name of Nobel Prize–winning physicist Leo Esaki, known for his pioneering work on quantum tunneling and semiconductor devices.
  • E. Mamoru
    Mamoru is a Japanese masculine given name commonly borne by notable figures in politics, arts, 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_69bd445d94788190b72e2cc563120995 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd78daab708190a42734a14dddb2fc completed March 20, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed0099afc8190badca81bd5efb8f6 completed March 21, 2026, 5:06 p.m.
NEDg Description generation batch_69bed3f4af288190beec97356b21f990 completed March 21, 2026, 5:23 p.m.
NED2 Entity disambiguation (via description) batch_69bed49625688190972acb1cb0c2a83b completed March 21, 2026, 5:25 p.m.
Created at: March 20, 2026, 1:44 p.m.