Triple

T18912772
Position Surface form Disambiguated ID Type / Status
Subject The Legend of Zelda: Skyward Sword E462647 entity
Predicate composer P1361 FINISHED
Object Takeshi Hama
Takeshi Hama is a Japanese video game composer best known for contributing to the soundtrack of Nintendo’s The Legend of Zelda: Skyward Sword.
E2292321 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: Takeshi Hama | Statement: [The Legend of Zelda: Skyward Sword, composer, Takeshi Hama]
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: Takeshi Hama
Triple: [The Legend of Zelda: Skyward Sword, composer, Takeshi Hama]
Generated description
Takeshi Hama is a Japanese video game composer best known for contributing to the soundtrack of Nintendo’s The Legend of Zelda: Skyward Sword.

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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c624516c81909e6bf04707d3c71c completed April 20, 2026, 6:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5ce418ddf88190a85416a79f7225fe completed July 19, 2026, 2:50 p.m.
NEDg Description generation batch_6a672da79a7481909b324f18b8d2649f completed July 27, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a683a3f71d08190a2b0af62998f9352 completed July 28, 2026, 5:12 a.m.
Created at: April 10, 2026, 11:58 a.m.