Triple

T33650311
Position Surface form Disambiguated ID Type / Status
Subject Lady of Holderness E862079 entity
Predicate hasGenderedFormOf P17779 FINISHED
Object Lord of Holderness
The Lord of Holderness is a noble title historically associated with the feudal lordship of the Holderness region in the East Riding of Yorkshire, England.
E2061080 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: Lord of Holderness | Statement: [Lady of Holderness, hasGenderedFormOf, Lord of Holderness]
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: Lord of Holderness
Triple: [Lady of Holderness, hasGenderedFormOf, Lord of Holderness]
Generated description
The Lord of Holderness is a noble title historically associated with the feudal lordship of the Holderness region in the East Riding of Yorkshire, 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_69f349840ba881908e3bfce536aeb92b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f9c168608190a7fd52f3fcb4b2ad completed May 3, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36271db1548190bb1ccf04d2e1a55c completed June 20, 2026, 5:37 a.m.
NEDg Description generation batch_6a3628077de08190af490293002fb49d completed June 20, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_6a36290ab68081908c16a32eac142a8d completed June 20, 2026, 5:45 a.m.
Created at: May 1, 2026, 1:42 a.m.