Triple

T30123319
Position Surface form Disambiguated ID Type / Status
Subject Lentulus E765616 entity
Predicate borneBy P2834 FINISHED
Object Publius Cornelius Lentulus Scipio
Publius Cornelius Lentulus Scipio was a Roman senator and consul from the prominent patrician Cornelii Scipiones family during the late Republic.
E1920840 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: Publius Cornelius Lentulus Scipio | Statement: [Lentulus, borneBy, Publius Cornelius Lentulus Scipio]
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: Publius Cornelius Lentulus Scipio
Triple: [Lentulus, borneBy, Publius Cornelius Lentulus Scipio]
Generated description
Publius Cornelius Lentulus Scipio was a Roman senator and consul from the prominent patrician Cornelii Scipiones family during the late Republic.

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_69f2247716748190ae4f16998f49ddf1 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67deccfe08190963db977b17c8ab4 completed May 2, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2856da6ee081909b8bfe337b4297d4 completed June 9, 2026, 6:09 p.m.
NEDg Description generation batch_6a28585a2960819096d4e59ad210a0da completed June 9, 2026, 6:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2859680d408190bd5a293365a92f47 completed June 9, 2026, 6:20 p.m.
Created at: April 29, 2026, 7:13 p.m.