Triple

T26209366
Position Surface form Disambiguated ID Type / Status
Subject Henry Wyatt E655440 entity
Predicate propertyOwned P9016 FINISHED
Object Boxley Abbey estates
Boxley Abbey estates were the former monastic lands of Boxley Abbey in Kent, England, later held as a country estate by figures such as Tudor courtier Sir Henry Wyatt.
E1714420 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: Boxley Abbey estates | Statement: [Henry Wyatt, propertyOwned, Boxley Abbey estates]
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: Boxley Abbey estates
Triple: [Henry Wyatt, propertyOwned, Boxley Abbey estates]
Generated description
Boxley Abbey estates were the former monastic lands of Boxley Abbey in Kent, England, later held as a country estate by figures such as Tudor courtier Sir Henry Wyatt.

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_69ee5b49adb4819086545280d4ef6337 completed April 26, 2026, 6:36 p.m.
NER Named-entity recognition batch_69f60d160f60819087ee6aac626327ea completed May 2, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a118589a968819083a0155f6cd682e2 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a1186b5863c81909864e1a749756793 completed May 23, 2026, 10:51 a.m.
NED2 Entity disambiguation (via description) batch_6a11872d97908190980c44ddb6820d50 completed May 23, 2026, 10:53 a.m.
Created at: April 26, 2026, 8:51 p.m.