Triple

T26155639
Position Surface form Disambiguated ID Type / Status
Subject Sleepwalk with Me E659950 entity
Predicate hasCharacter P2308 FINISHED
Object Matt Pandamiglio
Matt Pandamiglio is the anxious, aspiring stand-up comedian and semi-autobiographical protagonist of Mike Birbiglia’s film and one-man show "Sleepwalk with Me."
E1988601 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: Matt Pandamiglio | Statement: [Sleepwalk with Me, hasCharacter, Matt Pandamiglio]
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: Matt Pandamiglio
Triple: [Sleepwalk with Me, hasCharacter, Matt Pandamiglio]
Generated description
Matt Pandamiglio is the anxious, aspiring stand-up comedian and semi-autobiographical protagonist of Mike Birbiglia’s film and one-man show "Sleepwalk with Me."

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_69ee5bc5a9908190899d39ce95c6d215 completed April 26, 2026, 6:39 p.m.
NER Named-entity recognition batch_69f60c0fd6a08190bafd573b07bb2fe8 completed May 2, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2ed4bccf5c81909337842e7249f2af completed June 14, 2026, 4:20 p.m.
NEDg Description generation batch_6a2ed5c07e34819098385a0d7a928fa4 completed June 14, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_6a2ed7379d088190b7481d5c7eb61b9f completed June 14, 2026, 4:30 p.m.
Created at: April 26, 2026, 8:27 p.m.