Triple

T25031291
Position Surface form Disambiguated ID Type / Status
Subject ceremonial county of Shropshire E626848 entity
Predicate borderedBy P224 FINISHED
Object ceremonial county of Wrexham
The ceremonial county of Wrexham is an area in north-east Wales centered on the city of Wrexham, known for its industrial heritage, market town history, and position near the English border.
E1662077 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: ceremonial county of Wrexham | Statement: [ceremonial county of Shropshire, borderedBy, ceremonial county of Wrexham]
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: ceremonial county of Wrexham
Triple: [ceremonial county of Shropshire, borderedBy, ceremonial county of Wrexham]
Generated description
The ceremonial county of Wrexham is an area in north-east Wales centered on the city of Wrexham, known for its industrial heritage, market town history, and position near the English border.

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_69e2ff2a2c088190be513727ee8bfe78 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44f6fcab081909470c94a5f519d79 completed May 1, 2026, 7 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1048bb7b088190b48ca45a4f6dfc2f completed May 22, 2026, 12:14 p.m.
NEDg Description generation batch_6a1049b63de881908e04b30b555d7809 completed May 22, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_6a104aa15f248190ba69524b7d516bc1 completed May 22, 2026, 12:22 p.m.
Created at: April 18, 2026, 6:07 a.m.