Triple

T32201965
Position Surface form Disambiguated ID Type / Status
Subject Jun Matsumoto E822561 entity
Predicate hasRole P161 FINISHED
Object Momo in Kimi wa Petto
Momo in Kimi wa Petto is the charming, younger live-in "pet" and love interest of the heroine in the Japanese drama and manga series Kimi wa Petto.
 E1998025 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: Momo in Kimi wa Petto | Statement: [Jun Matsumoto, hasRole, Momo in Kimi wa Petto]
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: Momo in Kimi wa Petto
Triple: [Jun Matsumoto, hasRole, Momo in Kimi wa Petto]
Generated description
Momo in Kimi wa Petto is the charming, younger live-in "pet" and love interest of the heroine in the Japanese drama and manga series Kimi wa Petto.

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_69f349093174819086e633c190a51aa8 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bb3c8d7081909b960e469e4d8504 completed May 3, 2026, 3:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f3b90c60c81908055561e317e7704 completed June 14, 2026, 11:38 p.m.
NEDg Description generation batch_6a2f3c35079c8190a9b5d359d16cfd8b completed June 14, 2026, 11:41 p.m.
NED2 Entity disambiguation (via description) batch_6a2f41a090a08190ae41dff8c3b1a4a6 completed June 15, 2026, 12:04 a.m.
Created at: May 1, 2026, 12:36 a.m.