Triple

T25900817
Position Surface form Disambiguated ID Type / Status
Subject Super Paper Mario E652607 entity
Predicate character P662 FINISHED
Object Mimi
Mimi is a recurring shape-shifting antagonist in the video game Super Paper Mario, known for her spider-like form and obsession with money.
E1709647 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: Mimi | Statement: [Super Paper Mario, character, Mimi]
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: Mimi
Triple: [Super Paper Mario, character, Mimi]
Generated description
Mimi is a recurring shape-shifting antagonist in the video game Super Paper Mario, known for her spider-like form and obsession with money.

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_69e7ab3c6cc081908de59bfcc28ec19d completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6038950948190a64ecb98ebcca94b completed May 2, 2026, 2 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11273090bc8190b1067ade0eedca9b completed May 23, 2026, 4:04 a.m.
NEDg Description generation batch_6a1134d90aa88190b68f50cbac9c6944 completed May 23, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_6a113610d1d8819097ce5070e47a7645 completed May 23, 2026, 5:07 a.m.
Created at: April 22, 2026, 8:24 a.m.