Triple

T11749653
Position Surface form Disambiguated ID Type / Status
Subject Sesshū Tōyō E279372 entity
Predicate givenName P17 FINISHED
Object Tōyō
Tōyō is the given name of Sesshū Tōyō, a renowned Japanese Zen Buddhist monk and master of ink painting during the Muromachi period.
E944846 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: Tōyō | Statement: [Sesshū Tōyō, givenName, Tōyō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tōyō
Context triple: [Sesshū Tōyō, givenName, Tōyō]
  • A. Takara
    Takara is a Japanese toy company best known for creating and producing Transformers and other popular action figures.
  • B. Mibuchi
    Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
  • C. Nisshin
    Nisshin is a suburban city in central Japan known for its residential communities and proximity to Nagoya in Aichi Prefecture.
  • D. Meitetsu
    Meitetsu is a major private railway company in Japan’s Chubu region, best known for operating extensive rail and transport services centered around Nagoya.
  • E. Nihondaira
    Nihondaira is a scenic plateau in Shizuoka Prefecture, Japan, famed for its panoramic views of Mount Fuji, Suruga Bay, and the surrounding tea fields.
  • 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: Tōyō
Triple: [Sesshū Tōyō, givenName, Tōyō]
Generated description
Tōyō is the given name of Sesshū Tōyō, a renowned Japanese Zen Buddhist monk and master of ink painting during the Muromachi period.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tōyō
Target entity description: Tōyō is the given name of Sesshū Tōyō, a renowned Japanese Zen Buddhist monk and master of ink painting during the Muromachi period.
  • A. Takara
    Takara is a Japanese toy company best known for creating and producing Transformers and other popular action figures.
  • B. Mibuchi
    Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
  • C. Nisshin
    Nisshin is a suburban city in central Japan known for its residential communities and proximity to Nagoya in Aichi Prefecture.
  • D. Meitetsu
    Meitetsu is a major private railway company in Japan’s Chubu region, best known for operating extensive rail and transport services centered around Nagoya.
  • E. Nihondaira
    Nihondaira is a scenic plateau in Shizuoka Prefecture, Japan, famed for its panoramic views of Mount Fuji, Suruga Bay, and the surrounding tea fields.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a508b0c4819082fbcc27d559ea2f completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a0492b48190b6f2e3cf36b4f537 completed April 28, 2026, 2:23 a.m.
NEDg Description generation batch_69f0319520dc8190817c5e75ddb7d40b completed April 28, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_69f05ad36e4c8190b7239e5b33713369 completed April 28, 2026, 6:59 a.m.
Created at: April 8, 2026, 9:41 p.m.