Triple

T28770164
Position Surface form Disambiguated ID Type / Status
Subject Dumb and Dumberer: When Harry Met Lloyd E726388 entity
Predicate screenwriter P2831 FINISHED
Object Barry Wernick
Barry Wernick is an American screenwriter best known for co-writing the comedy prequel film "Dumb and Dumberer: When Harry Met Lloyd."
E1834593 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: Barry Wernick | Statement: [Dumb and Dumberer: When Harry Met Lloyd, screenwriter, Barry Wernick]
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: Barry Wernick
Triple: [Dumb and Dumberer: When Harry Met Lloyd, screenwriter, Barry Wernick]
Generated description
Barry Wernick is an American screenwriter best known for co-writing the comedy prequel film "Dumb and Dumberer: When Harry Met Lloyd."

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_69f03198be14819098fa74e48b3749bf completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65827a4fc8190b0bd1914655502d6 completed May 2, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a26586b48190b1a011bdecd38a46 completed June 6, 2026, 10:42 p.m.
NEDg Description generation batch_6a24ad71258c8190971169f6a4363d45 completed June 6, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a24b1a8bef08190a970dd2d64092f56 completed June 6, 2026, 11:47 p.m.
Created at: April 28, 2026, 6:15 a.m.