Triple

T37683549
Position Surface form Disambiguated ID Type / Status
Subject Pope Sylvester II E938302 entity
Predicate notableWork P4 FINISHED
Object De rationali et ratione uti
De rationali et ratione uti is a medieval philosophical treatise by Pope Sylvester II that explores the nature of reason and its proper use in human understanding.
E2239853 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: De rationali et ratione uti | Statement: [Pope Sylvester II, notableWork, De rationali et ratione uti]
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: De rationali et ratione uti
Triple: [Pope Sylvester II, notableWork, De rationali et ratione uti]
Generated description
De rationali et ratione uti is a medieval philosophical treatise by Pope Sylvester II that explores the nature of reason and its proper use in human understanding.

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_69f76ed881408190bc62a969530a4a53 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbadfb67f8819097ea0abeb0f916f7 completed May 6, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40cdb8bc8c8190bef3228ad7ddb7df completed June 28, 2026, 7:31 a.m.
NEDg Description generation batch_6a40cf18930c819099267b4a012d7873 completed June 28, 2026, 7:36 a.m.
NED2 Entity disambiguation (via description) batch_6a40d1ade62c81908824f28dbdf2e129 completed June 28, 2026, 7:47 a.m.
Created at: May 3, 2026, 4:18 p.m.