Triple

T1282038
Position Surface form Disambiguated ID Type / Status
Subject Masaharu Homma E27347 entity
Predicate familyName P18 FINISHED
Object Homma
Homma is a Japanese surname borne by various notable individuals across fields such as the military, arts, and sports.
 E214440 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: Homma | Statement: [Masaharu Homma, familyName, Homma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Homma
Context triple: [Masaharu Homma, familyName, Homma]
  • A. Sannomiya
    Sannomiya is a major commercial and transportation hub in central Kobe, Japan, known for its shopping streets, nightlife, and role as the city’s downtown core.
  • B. Kumiai
    Kumiai is an indigenous Yuman language spoken by the Kumeyaay people in the border region of southern California and northern Baja California.
  • C. Kamitsumaki
    Kamitsumaki is the first volume of the ancient Japanese chronicle Kojiki, focusing on Shinto creation myths and the age of the gods.
  • D. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • E. Habikino
    Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
  • 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: Homma
Triple: [Masaharu Homma, familyName, Homma]
Generated description
Homma is a Japanese surname borne by various notable individuals across fields such as the military, arts, and sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Homma
Target entity description: Homma is a Japanese surname borne by various notable individuals across fields such as the military, arts, and sports.
  • A. Sannomiya
    Sannomiya is a major commercial and transportation hub in central Kobe, Japan, known for its shopping streets, nightlife, and role as the city’s downtown core.
  • B. Kumiai
    Kumiai is an indigenous Yuman language spoken by the Kumeyaay people in the border region of southern California and northern Baja California.
  • C. Kamitsumaki
    Kamitsumaki is the first volume of the ancient Japanese chronicle Kojiki, focusing on Shinto creation myths and the age of the gods.
  • D. Tatsuno
    Tatsuno is a city in western Japan known for its traditional soy sauce production and historic townscape within Hyogo Prefecture.
  • E. Habikino
    Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
  • 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b317788190a1672b5ee422a049 completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf3ab00888190afc7c54d9b89ae3b completed March 8, 2026, 10:09 p.m.
NEDg Description generation batch_69adf452ab488190b5d57e3b04159408 completed March 8, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69adf4bdb6dc8190964e5e78abfb8e40 completed March 8, 2026, 10:14 p.m.
Created at: March 1, 2026, 7:50 p.m.