Triple

T20350125
Position Surface form Disambiguated ID Type / Status
Subject Chrono Trigger E495983 entity
Predicate director P255 FINISHED
Object Takashi Tokita
Takashi Tokita is a Japanese video game designer and director best known for his work on influential Square Enix role-playing games such as Chrono Trigger and the Final Fantasy series.
E2294064 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: Takashi Tokita | Statement: [Chrono Trigger, director, Takashi Tokita]
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: Takashi Tokita
Triple: [Chrono Trigger, director, Takashi Tokita]
Generated description
Takashi Tokita is a Japanese video game designer and director best known for his work on influential Square Enix role-playing games such as Chrono Trigger and the Final Fantasy 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_69e0b4a3320881909495ae8bc30bc2dc completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6784eacf4819095504e541d1d284d completed April 20, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7b70e3e8f88190a9ad683857924b32 completed Aug. 11, 2026, 6:58 p.m.
NEDg Description generation batch_6a7b7167206481908b7096fea54c11ec completed Aug. 11, 2026, 7 p.m.
NED2 Entity disambiguation (via description) batch_6a7b71bf6b44819084224d022f9ca2be completed Aug. 11, 2026, 7:02 p.m.
Created at: April 16, 2026, 11:24 a.m.