Triple

T32099177
Position Surface form Disambiguated ID Type / Status
Subject Byzantine Platonism E819796 entity
Predicate hasKeyFigure P810 FINISHED
Object George Chrysokokkes
George Chrysokokkes was a Byzantine scholar and philosopher noted for his contributions to the Platonic intellectual tradition within late Byzantine thought.
E2026102 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 Chrysokokkes | Statement: [Byzantine Platonism, hasKeyFigure, George Chrysokokkes]
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 Chrysokokkes
Triple: [Byzantine Platonism, hasKeyFigure, George Chrysokokkes]
Generated description
George Chrysokokkes was a Byzantine scholar and philosopher noted for his contributions to the Platonic intellectual tradition within late Byzantine thought.

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_69f34901106881908ea893ad504a08be completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b647a7a88190aeef1b9b1e2d5f3b completed May 3, 2026, 2:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34bcd0954c81908532b634314a5cb7 completed June 19, 2026, 3:51 a.m.
NEDg Description generation batch_6a34bdffef808190ad2ae81a27161b7a completed June 19, 2026, 3:56 a.m.
NED2 Entity disambiguation (via description) batch_6a34bebf945481908a7d8938bfe50654 completed June 19, 2026, 3:59 a.m.
Created at: May 1, 2026, 12:26 a.m.