Triple

T17363732
Position Surface form Disambiguated ID Type / Status
Subject Rebirth of Mothra E422134 entity
Predicate writer P1360 FINISHED
Object Masumi Suetani
Masumi Suetani is a Japanese screenwriter best known for his work on the kaiju fantasy film "Rebirth of Mothra."
E1855097 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: Masumi Suetani | Statement: [Rebirth of Mothra, writer, Masumi Suetani]
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: Masumi Suetani
Triple: [Rebirth of Mothra, writer, Masumi Suetani]
Generated description
Masumi Suetani is a Japanese screenwriter best known for his work on the kaiju fantasy film "Rebirth of Mothra."

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_69d889d520008190a26917a95bf1c2ea completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a4f52988190847230e119a35b87 completed April 19, 2026, 2:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a256988a21481908682d6b61b8e98d0 completed June 7, 2026, 12:52 p.m.
NEDg Description generation batch_6a256f31adfc8190b5c86993112f300a completed June 7, 2026, 1:16 p.m.
NED2 Entity disambiguation (via description) batch_6a256f98942081909d86856ade8b24be completed June 7, 2026, 1:18 p.m.
Created at: April 10, 2026, 5:44 a.m.