Triple

T28342081
Position Surface form Disambiguated ID Type / Status
Subject Highgate Underground Station E717840 entity
Predicate servesArea P82 FINISHED
Object Archway Road area
The Archway Road area is a district in north London centered around the A1 Archway Road, known for its mix of residential streets, local shops, and proximity to Highgate and surrounding green spaces.
E570854 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: Archway Road area | Statement: [Highgate Underground Station, servesArea, Archway Road area]
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: Archway Road area
Triple: [Highgate Underground Station, servesArea, Archway Road area]
Generated description
The Archway Road area is a district in north London centered around the A1 Archway Road, known for its mix of residential streets, local shops, and proximity to Highgate and surrounding green spaces.

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_69eff6eb30388190b898b96c4be6f49d completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64bd8d1848190835efdf5020b54cb completed May 2, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1627bec9ac819094444c5b5130ceb8 completed May 26, 2026, 11:07 p.m.
NEDg Description generation batch_6a162a68838481908eed21663497c78a completed May 26, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_6a162af3b7308190851819d6989be119 completed May 26, 2026, 11:21 p.m.
Created at: April 28, 2026, 12:40 a.m.