Triple

T31321385
Position Surface form Disambiguated ID Type / Status
Subject Toei Animation E798750 entity
Predicate formerName P65 FINISHED
Object Toei Doga
Toei Doga is the former name of Toei Animation, a major Japanese studio known for producing many iconic anime series and films.
E1956196 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: Toei Doga | Statement: [Toei Animation, formerName, Toei Doga]
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: Toei Doga
Triple: [Toei Animation, formerName, Toei Doga]
Generated description
Toei Doga is the former name of Toei Animation, a major Japanese studio known for producing many iconic anime series and films.

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_69f224e3238c8190b2291f50ea4962cd completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69ead17348190b059f333ca055465 completed May 3, 2026, 1:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a1e47878481909be2b47fe582b66f completed June 11, 2026, 2:32 a.m.
NEDg Description generation batch_6a2a1f9e28b88190a979f7dff57a0280 completed June 11, 2026, 2:38 a.m.
NED2 Entity disambiguation (via description) batch_6a2a201ba4b48190afe941c045368274 completed June 11, 2026, 2:40 a.m.
Created at: April 29, 2026, 9:15 p.m.