Triple

T2137182
Position Surface form Disambiguated ID Type / Status
Subject Eishiro Saito E46680 entity
Predicate familyName P18 FINISHED
Object Saito
Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
 E339085 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: Saito | Statement: [Eishiro Saito, familyName, Saito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saito
Context triple: [Eishiro Saito, familyName, Saito]
  • A. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • B. Sakae
    Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
  • C. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • D. Satō
    Satō is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and other fields.
  • E. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • 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: Saito
Triple: [Eishiro Saito, familyName, Saito]
Generated description
Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saito
Target entity description: Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
  • A. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • B. Sakae
    Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
  • C. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • D. Satō
    Satō is a common Japanese surname borne by numerous notable figures in politics, arts, sports, and other fields.
  • E. Nishiwaki
    Nishiwaki is a city in central Hyōgo Prefecture, Japan, known for its location near the geographic center of the country and its mix of industrial and rural landscapes.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbdff9254819094d27405478e29a0 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69b276a3cfa48190b0ecee43d24046e6 completed March 12, 2026, 8:17 a.m.
NEDg Description generation batch_69b2778f5d848190b5ae405f3e777992 completed March 12, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69b27879ff6081909f7d7f474d46ac4b completed March 12, 2026, 8:25 a.m.
Created at: March 4, 2026, 7:44 p.m.