Triple

T38525507
Position Surface form Disambiguated ID Type / Status
Subject Cuthwine of Wessex E922616 entity
Predicate child P120 FINISHED
Object Cutha of Wessex
Cutha of Wessex was an early Anglo-Saxon prince of the West Saxons, known primarily as a member of the royal House of Wessex and part of the dynasty that preceded the later kings of England.
E922616 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: Cutha of Wessex | Statement: [Cuthwine of Wessex, child, Cutha of Wessex]
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: Cutha of Wessex
Triple: [Cuthwine of Wessex, child, Cutha of Wessex]
Generated description
Cutha of Wessex was an early Anglo-Saxon prince of the West Saxons, known primarily as a member of the royal House of Wessex and part of the dynasty that preceded the later kings of England.

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_69f76ea5f5588190bd0b28c82e975640 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd2b4cd58819098ab421391de7dc4 completed May 7, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a423419d0e881909f3d5a1990bb8a43 completed June 29, 2026, 9 a.m.
NEDg Description generation batch_6a4234e9228c8190a9de309d092e6646 completed June 29, 2026, 9:03 a.m.
NED2 Entity disambiguation (via description) batch_6a423629cebc8190ac85a6a7dc22a1bf completed June 29, 2026, 9:08 a.m.
Created at: May 3, 2026, 4:32 p.m.