Triple

T30349084
Position Surface form Disambiguated ID Type / Status
Subject Girls Dead Monster E771941 entity
Predicate hasMember P10 FINISHED
Object Sekine
Sekine is a fictional musician and supporting character who plays in the in-story band Girls Dead Monster from the anime series "Angel Beats!".
E2045239 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: Sekine | Statement: [Girls Dead Monster, hasMember, Sekine]
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: Sekine
Triple: [Girls Dead Monster, hasMember, Sekine]
Generated description
Sekine is a fictional musician and supporting character who plays in the in-story band Girls Dead Monster from the anime series "Angel Beats!".

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_69f2248b9a208190bc3e6804acd5afd6 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6820a250c8190ba7afa43f6f55c46 completed May 2, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3542f5dd1c819096ff0e700a89c853 completed June 19, 2026, 1:24 p.m.
NEDg Description generation batch_6a3543e33234819098c6be618c0a4404 completed June 19, 2026, 1:28 p.m.
NED2 Entity disambiguation (via description) batch_6a35446396788190b2acad4c36a8226f completed June 19, 2026, 1:30 p.m.
Created at: April 29, 2026, 7:56 p.m.