Triple

T20217838
Position Surface form Disambiguated ID Type / Status
Subject The Legend of Zelda: Tears of the Kingdom E495173 entity
Predicate writer P1360 FINISHED
Object Akihito Toda
Akihito Toda is a Japanese video game writer best known for his scenario and script work on major Nintendo titles, including entries in The Legend of Zelda series.
E2293882 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: Akihito Toda | Statement: [The Legend of Zelda: Tears of the Kingdom, writer, Akihito Toda]
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: Akihito Toda
Triple: [The Legend of Zelda: Tears of the Kingdom, writer, Akihito Toda]
Generated description
Akihito Toda is a Japanese video game writer best known for his scenario and script work on major Nintendo titles, including entries in The Legend of Zelda series.

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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66edaeeb08190bb74bd4a10aceca2 completed April 20, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7b26b04dbc8190862aa6b8f7ef34cc completed Aug. 11, 2026, 1:42 p.m.
NEDg Description generation batch_6a7b2709c6988190a4ad582df1e3cf99 completed Aug. 11, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_6a7b5191f0ac8190b181a347a3542e1f completed Aug. 11, 2026, 4:45 p.m.
Created at: April 11, 2026, 11:39 p.m.