Triple

T11932357
Position Surface form Disambiguated ID Type / Status
Subject Takeda Shingen E283944 entity
Predicate spouse P13 FINISHED
Object Sanjo
Sanjo was a Japanese noblewoman best known as the principal wife of the Sengoku-period warlord Takeda Shingen.
 E1216497 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: Sanjo | Statement: [Takeda Shingen, spouse, Sanjo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sanjo
Context triple: [Takeda Shingen, spouse, Sanjo]
  • A. Saijo
    Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
  • B. Shichirōji
    Shichirōji is a seasoned, loyal samurai and former comrade of Kambei in Akira Kurosawa’s film "Seven Samurai," known for his calm demeanor and steadfast bravery.
  • C. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • D. Kamishihoro
    Kamishihoro is a town in Hokkaido, Japan, known for its natural scenery, hot springs, and the historic Taushubetsu River Bridge within the Daisetsuzan mountain region.
  • E. Akiruno
    Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
  • 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: Sanjo
Triple: [Takeda Shingen, spouse, Sanjo]
Generated description
Sanjo was a Japanese noblewoman best known as the principal wife of the Sengoku-period warlord Takeda Shingen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sanjo
Target entity description: Sanjo was a Japanese noblewoman best known as the principal wife of the Sengoku-period warlord Takeda Shingen.
  • A. Saijo
    Saijo is a city in Ehime Prefecture on Japan’s Shikoku island, known for its industrial facilities and maritime-related industries.
  • B. Shichirōji
    Shichirōji is a seasoned, loyal samurai and former comrade of Kambei in Akira Kurosawa’s film "Seven Samurai," known for his calm demeanor and steadfast bravery.
  • C. Fujinomiya
    Fujinomiya is a city in Shizuoka Prefecture, Japan, known as a major gateway to Mount Fuji and for its scenic views of the iconic volcano.
  • D. Kamishihoro
    Kamishihoro is a town in Hokkaido, Japan, known for its natural scenery, hot springs, and the historic Taushubetsu River Bridge within the Daisetsuzan mountain region.
  • E. Akiruno
    Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90305015c81908edb0d9d3d012b2e completed April 10, 2026, 2:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a005804f5c08190b545bc8b65e953f7 completed May 10, 2026, 10:03 a.m.
NEDg Description generation batch_6a00592562708190ae88f24fb34c7a02 completed May 10, 2026, 10:08 a.m.
NED2 Entity disambiguation (via description) batch_6a005a17fd648190b2c6843f47a9ee2c completed May 10, 2026, 10:12 a.m.
Created at: April 8, 2026, 9:45 p.m.