Triple

T21188866
Position Surface form Disambiguated ID Type / Status
Subject Fire Emblem Warriors E522158 entity
Predicate composer P1361 FINISHED
Object Masato Kouda
Masato Kouda is a Japanese video game composer known for his dynamic, rock-influenced soundtracks on titles such as the Devil May Cry series and various action and role-playing games.
E1635947 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: Masato Kouda | Statement: [Fire Emblem Warriors, composer, Masato Kouda]
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: Masato Kouda
Triple: [Fire Emblem Warriors, composer, Masato Kouda]
Generated description
Masato Kouda is a Japanese video game composer known for his dynamic, rock-influenced soundtracks on titles such as the Devil May Cry series and various action and role-playing games.

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_69e0b51061388190aa03f19700d3ef04 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e733350e588190a31467758a8afa5c completed April 21, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe32a973481908e9297b36f764aa3 completed May 22, 2026, 5:01 a.m.
NEDg Description generation batch_6a0fe740419481908c160ac1787e769a completed May 22, 2026, 5:18 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe7a50e44819087fe4d62bae72ec0 completed May 22, 2026, 5:20 a.m.
Created at: April 16, 2026, 3:07 p.m.