Triple

T21578591
Position Surface form Disambiguated ID Type / Status
Subject Audley, Staffordshire E532463 entity
Predicate hasNeighbouringVillage P22613 FINISHED
Object Wood Lane
Wood Lane is a small rural village in Staffordshire, England, situated near the village of Audley.
E2244487 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: Wood Lane | Statement: [Audley, Staffordshire, hasNeighbouringVillage, Wood Lane]
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: Wood Lane
Triple: [Audley, Staffordshire, hasNeighbouringVillage, Wood Lane]
Generated description
Wood Lane is a small rural village in Staffordshire, England, situated near the village of Audley.

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_69e0c4618bec8190bcb0feb74568cbb1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb5ac1048190aa45d7d3c780b5c9 completed April 27, 2026, 4:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a40fb5d9a448190808c8fba124ef699 completed June 28, 2026, 10:45 a.m.
NEDg Description generation batch_6a40fbf76f28819084cae2d29252ac84 completed June 28, 2026, 10:48 a.m.
NED2 Entity disambiguation (via description) batch_6a40fc8326d48190bd0b3602ecac7dfd completed June 28, 2026, 10:50 a.m.
Created at: April 16, 2026, 6:31 p.m.