Triple

T35441298
Position Surface form Disambiguated ID Type / Status
Subject Kurono Kei E1024345 entity
Predicate ally P4662 FINISHED
Object Reika Shimohira
Reika Shimohira is a popular idol and skilled fighter in the manga and anime series "Gantz," known for her complex relationship with protagonist Kurono Kei and her role in the deadly missions.
E2290023 NE FINISHED

How this triple was built (2 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: Reika Shimohira | Statement: [Kurono Kei, ally, Reika Shimohira]
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: Reika Shimohira
Triple: [Kurono Kei, ally, Reika Shimohira]
Generated description
Reika Shimohira is a popular idol and skilled fighter in the manga and anime series "Gantz," known for her complex relationship with protagonist Kurono Kei and her role in the deadly missions.

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_69f76df8089481909f0018266ee881b7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f795c200f48190a596f34fdae23fd7 completed May 3, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5b8c22c4808190b378aac178b9f2ba completed July 18, 2026, 2:22 p.m.
NEDg Description generation batch_6a5b8d096adc8190be8736dd9972d63c completed July 18, 2026, 2:26 p.m.
NED2 Entity disambiguation (via description) batch_6a5b8db62af48190888af33af20d355e completed July 18, 2026, 2:29 p.m.
Created at: May 3, 2026, 4:04 p.m.