Triple

T30154489
Position Surface form Disambiguated ID Type / Status
Subject Brodmann area 41 E766486 entity
Predicate namedAfter P63 FINISHED
Object Korbinian Brodmann
Korbinian Brodmann was a German neurologist and neuroanatomist renowned for his influential cytoarchitectonic mapping of the cerebral cortex into numbered areas now known as Brodmann areas.
E1902178 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: Korbinian Brodmann | Statement: [Brodmann area 41, namedAfter, Korbinian Brodmann]
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: Korbinian Brodmann
Triple: [Brodmann area 41, namedAfter, Korbinian Brodmann]
Generated description
Korbinian Brodmann was a German neurologist and neuroanatomist renowned for his influential cytoarchitectonic mapping of the cerebral cortex into numbered areas now known as Brodmann areas.

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_69f22479cd088190ab4c6f3fce39d1c5 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ed66ab48190928ceb36710c1ed2 completed May 2, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274cc2c97c8190bc6206f4e0519079 completed June 8, 2026, 11:14 p.m.
NEDg Description generation batch_6a274ddf8d688190b480d115456651c3 completed June 8, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_6a274eb19fd48190a2d38ace0cc22b77 completed June 8, 2026, 11:22 p.m.
Created at: April 29, 2026, 7:20 p.m.