Triple

T38671189
Position Surface form Disambiguated ID Type / Status
Subject A Taste of My Own Medicine E940593 entity
Predicate author P4 FINISHED
Object Edward E. Rosenbaum
Edward E. Rosenbaum was an American physician and author best known for writing the memoir that inspired the film "The Doctor."
 E2293144 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: Edward E. Rosenbaum | Statement: [A Taste of My Own Medicine, author, Edward E. Rosenbaum]
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: Edward E. Rosenbaum
Triple: [A Taste of My Own Medicine, author, Edward E. Rosenbaum]
Generated description
Edward E. Rosenbaum was an American physician and author best known for writing the memoir that inspired the film "The Doctor."

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_69f76edfde348190bf6529d9f49ecd62 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdc13e4b081908123167772acdd7d completed May 7, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a6c1e2eb08190a9c35e3165ad8906 completed Aug. 11, 2026, 12:26 a.m.
NEDg Description generation batch_6a7a6c8b55ac8190b0ccd22d9e82874d completed Aug. 11, 2026, 12:27 a.m.
NED2 Entity disambiguation (via description) batch_6a7a6cd89a70819080d7292940bb3e43 completed Aug. 11, 2026, 12:29 a.m.
Created at: May 3, 2026, 4:33 p.m.