Triple

T3531438
Position Surface form Disambiguated ID Type / Status
Subject Iwakura Tomomi E74669 entity
Predicate givenName P17 FINISHED
Object Tomomi
Tomomi is a Japanese given name that can be used for people of any gender.
 E366139 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: Tomomi | Statement: [Iwakura Tomomi, givenName, Tomomi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tomomi
Context triple: [Iwakura Tomomi, givenName, Tomomi]
  • A. Tomoyuki
    Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
  • B. Totsuko
    Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
  • C. Itami
    Itami is a city in Hyōgo Prefecture, Japan, known for hosting Osaka International Airport (commonly called Itami Airport).
  • D. 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.
  • E. Tarō
    Tarō is a common Japanese masculine given name, often written with kanji meaning "eldest son" and frequently used in traditional and modern Japanese culture.
  • 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: Tomomi
Triple: [Iwakura Tomomi, givenName, Tomomi]
Generated description
Tomomi is a Japanese given name that can be used for people of any gender.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tomomi
Target entity description: Tomomi is a Japanese given name that can be used for people of any gender.
  • A. Tomoyuki
    Tomoyuki is a Japanese masculine given name borne by various notable figures in fields such as the military, arts, and entertainment.
  • B. Totsuko
    Totsuko is the former abbreviated name of Tokyo Tsushin Kogyo, the Japanese company that later became Sony.
  • C. Itami
    Itami is a city in Hyōgo Prefecture, Japan, known for hosting Osaka International Airport (commonly called Itami Airport).
  • D. 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.
  • E. Tarō
    Tarō is a common Japanese masculine given name, often written with kanji meaning "eldest son" and frequently used in traditional and modern Japanese culture.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc988ee081909c6b9d5eed0d2d6d completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e9a2b848190a5c2b3072fa6c44c completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37f07ab70819089fdb7083b81b992 completed March 13, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_69b38078bc288190b69d73a64acce8ca completed March 13, 2026, 3:11 a.m.
Created at: March 8, 2026, 3:19 p.m.