Triple

T29020884
Position Surface form Disambiguated ID Type / Status
Subject Simpsons Roasting on an Open Fire E737447 entity
Predicate writer P1360 FINISHED
Object Mimi Pond
Mimi Pond is an American cartoonist, writer, and humorist best known for her work in comics and for writing the premiere episode of the long-running animated series The Simpsons.
E1872793 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 Pond | Statement: [Simpsons Roasting on an Open Fire, writer, Mimi Pond]
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 Pond
Triple: [Simpsons Roasting on an Open Fire, writer, Mimi Pond]
Generated description
Mimi Pond is an American cartoonist, writer, and humorist best known for her work in comics and for writing the premiere episode of the long-running animated series The Simpsons.

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_69f077ee19f881909af48f9cab00a2e5 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f66005ea00819085501231fe82cc5e completed May 2, 2026, 8:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260bfbd67c8190944af3cc0eb77d6a completed June 8, 2026, 12:25 a.m.
NEDg Description generation batch_6a26103b50948190a67b288cf9f474ce completed June 8, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a261bab40048190b31f5b12454bedbf completed June 8, 2026, 1:32 a.m.
Created at: April 28, 2026, 9:49 a.m.