Triple

T30688882
Position Surface form Disambiguated ID Type / Status
Subject Highgate Conservation Area E781262 entity
Predicate contains P35 FINISHED
Object Highgate High Street
Highgate High Street is the main historic shopping and commercial street in the north London village of Highgate, known for its period architecture and local independent businesses.
 E1932176 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: Highgate High Street | Statement: [Highgate Conservation Area, contains, Highgate High Street]
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: Highgate High Street
Triple: [Highgate Conservation Area, contains, Highgate High Street]
Generated description
Highgate High Street is the main historic shopping and commercial street in the north London village of Highgate, known for its period architecture and local independent businesses.

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_69f224a92f54819095499b4d32bd5134 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68b867934819084ed0f079eb81c99 completed May 2, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b080c4848190b7ec54af588b5ac8 completed June 10, 2026, 12:32 a.m.
NEDg Description generation batch_6a28b1cd9e78819093ff46123d12a12e completed June 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2b2c9fc8190af8deaeceb76e5f9 completed June 10, 2026, 12:41 a.m.
Created at: April 29, 2026, 8:33 p.m.