Triple

T35680833
Position Surface form Disambiguated ID Type / Status
Subject Fawkham E1031003 entity
Predicate ceremonialCounty P2713 FINISHED
Object Kent
Kent is a historic county in southeastern England, often called the "Garden of England" and known for its orchards, hop gardens, and coastal towns.
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: [Fawkham, ceremonialCounty, 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: [Fawkham, ceremonialCounty, Kent]
Generated description
Kent is a historic county in southeastern England, often called the "Garden of England" and known for its orchards, hop gardens, and coastal towns.

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_69f76e0bb6608190ad3a1880be54a17d completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79fe983d48190915b44d890293ab6 completed May 3, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387d06747881908be93c1b2c4f7631 completed June 22, 2026, 12:08 a.m.
NEDg Description generation batch_6a387d74b3188190800893daaac0ab77 completed June 22, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_6a387e258d4c8190aed32f33ec5d9dbe completed June 22, 2026, 12:13 a.m.
Created at: May 3, 2026, 4:05 p.m.