Triple

T19493625
Position Surface form Disambiguated ID Type / Status
Subject Harrell Medical Education Building E487713 entity
Predicate namedAfter P63 FINISHED
Object George T. Harrell
George T. Harrell was a pioneering American physician and medical educator recognized for founding and shaping modern medical education programs, including serving as the first dean of the University of Florida College of Medicine.
E1626858 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: George T. Harrell | Statement: [Harrell Medical Education Building, namedAfter, George T. Harrell]
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: George T. Harrell
Triple: [Harrell Medical Education Building, namedAfter, George T. Harrell]
Generated description
George T. Harrell was a pioneering American physician and medical educator recognized for founding and shaping modern medical education programs, including serving as the first dean of the University of Florida College of Medicine.

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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6349002788190afe7831d008d440f completed April 20, 2026, 2:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc98202248190a2e3ee03c4e7078a completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcade9db88190b79f8f03c9b5f51f completed May 22, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcb724a888190838a30e05e556421 completed May 22, 2026, 3:20 a.m.
Created at: April 10, 2026, 1:40 p.m.