Triple

T30263699
Position Surface form Disambiguated ID Type / Status
Subject My Super Ex-Girlfriend E769572 entity
Predicate character P662 FINISHED
Object Professor Bedlam
Professor Bedlam is the supervillain alter ego of Barry Edward Lambert, the nerdy former boyfriend of the heroine in the romantic superhero comedy film "My Super Ex-Girlfriend."
E1906799 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: Professor Bedlam | Statement: [My Super Ex-Girlfriend, character, Professor Bedlam]
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: Professor Bedlam
Triple: [My Super Ex-Girlfriend, character, Professor Bedlam]
Generated description
Professor Bedlam is the supervillain alter ego of Barry Edward Lambert, the nerdy former boyfriend of the heroine in the romantic superhero comedy film "My Super Ex-Girlfriend."

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_69f22484a5f48190b678cd607700bc82 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f680ab3ba481908d75676fef98820f completed May 2, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27645fbe1c8190bb5b87e0680bd0fa completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a27682a252c81909dd4146f9acbd77f completed June 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_6a2768d8683c8190afb8c6880178c7bf completed June 9, 2026, 1:14 a.m.
Created at: April 29, 2026, 7:42 p.m.