Triple

T24067910
Position Surface form Disambiguated ID Type / Status
Subject St Mary the Virgin Churchyard, Ripple, Kent E596140 entity
Predicate locatedIn P40 FINISHED
Object Kent
Kent is a county in southeastern England known for its historic towns, rural landscapes, and coastal areas, often referred to as the "Garden of England."
E5977 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: Kent | Statement: [St Mary the Virgin Churchyard, Ripple, Kent, locatedIn, Kent]
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: Kent
Triple: [St Mary the Virgin Churchyard, Ripple, Kent, locatedIn, Kent]
Generated description
Kent is a county in southeastern England known for its historic towns, rural landscapes, and coastal areas, often referred to as the "Garden 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_69e288c25c008190850cf447940ab181 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1da5c57e88190ba05cc41b8fd035a completed April 29, 2026, 10:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f963f887081908c14b05fa1c9ed32 completed May 21, 2026, 11:33 p.m.
NEDg Description generation batch_6a0f9802d1bc8190b3f47810e29ef246 completed May 21, 2026, 11:40 p.m.
NED2 Entity disambiguation (via description) batch_6a0f992af65c819085d30795965384cb completed May 21, 2026, 11:45 p.m.
Created at: April 17, 2026, 10:40 p.m.