Triple

T2088938
Position Surface form Disambiguated ID Type / Status
Subject Seiko Noda E32621 entity
Predicate familyName P18 FINISHED
Object Noda
Noda is a Japanese surname borne by various notable figures in politics, entertainment, and other fields.
 E346804 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: Noda | Statement: [Seiko Noda, familyName, Noda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Noda
Context triple: [Seiko Noda, familyName, Noda]
  • A. Omiya
    Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
  • B. Arima
    Arima is a borough and one of the major urban centers in eastern Trinidad, known for its cultural heritage and role as a commercial hub in Trinidad and Tobago.
  • C. Shōnan
    Shōnan is a coastal region in Kanagawa Prefecture, Japan, known for its beaches, surf culture, and views of Enoshima and Mount Fuji.
  • D. Ayabe
    Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
  • E. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • 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: Noda
Triple: [Seiko Noda, familyName, Noda]
Generated description
Noda is a Japanese surname borne by various notable figures in politics, entertainment, and other fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Noda
Target entity description: Noda is a Japanese surname borne by various notable figures in politics, entertainment, and other fields.
  • A. Omiya
    Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
  • B. Arima
    Arima is a borough and one of the major urban centers in eastern Trinidad, known for its cultural heritage and role as a commercial hub in Trinidad and Tobago.
  • C. Shōnan
    Shōnan is a coastal region in Kanagawa Prefecture, Japan, known for its beaches, surf culture, and views of Enoshima and Mount Fuji.
  • D. Ayabe
    Ayabe is a small city in the northern part of Japan’s Kyoto Prefecture, known for its rural landscapes, traditional industries, and spiritual retreat centers.
  • E. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • 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_69a885eba0708190999696a45cbec816 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba730a5c8190a85be72149574d79 completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2f39ad7488190a7604a113c2e2bb3 completed March 12, 2026, 5:10 p.m.
NEDg Description generation batch_69b2ff426a4c8190a75f6718c25ed15e completed March 12, 2026, 6 p.m.
NED2 Entity disambiguation (via description) batch_69b313b260348190aa3360a76327e636 completed March 12, 2026, 7:27 p.m.
Created at: March 4, 2026, 7:43 p.m.