Triple

T36248132
Position Surface form Disambiguated ID Type / Status
Subject N postcode area E891719 entity
Predicate coversNeighbourhood P141690 FINISHED
Object Friern Barnet
Friern Barnet is a suburban residential district in the London Borough of Barnet in north London, known for its mix of Victorian and Edwardian housing and local high-street amenities.
E2190866 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: Friern Barnet | Statement: [N postcode area, coversNeighbourhood, Friern Barnet]
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: Friern Barnet
Triple: [N postcode area, coversNeighbourhood, Friern Barnet]
Generated description
Friern Barnet is a suburban residential district in the London Borough of Barnet in north London, known for its mix of Victorian and Edwardian housing and local high-street amenities.

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_69f76e4599108190811532e707d6bc2c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fd4c90534c819099556f4b6aea606f completed May 8, 2026, 2:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a39f8f52ce08190ace8b657929478ef completed June 23, 2026, 3:09 a.m.
NEDg Description generation batch_6a39fbbcb73481908c4346df2900a03a completed June 23, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_6a39fc7cd3288190a17acf9a240987c7 completed June 23, 2026, 3:24 a.m.
Created at: May 3, 2026, 4:09 p.m.