Triple

T30316528
Position Surface form Disambiguated ID Type / Status
Subject Kentish Town Road E771068 entity
Predicate hasJunctionWith P1018 FINISHED
Object Prince of Wales Road
Prince of Wales Road is a street in the London Borough of Camden that runs through the Kentish Town and Chalk Farm area, connecting several major local roads and residential neighborhoods.
E2293663 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: Prince of Wales Road | Statement: [Kentish Town Road, hasJunctionWith, Prince of Wales Road]
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: Prince of Wales Road
Triple: [Kentish Town Road, hasJunctionWith, Prince of Wales Road]
Generated description
Prince of Wales Road is a street in the London Borough of Camden that runs through the Kentish Town and Chalk Farm area, connecting several major local roads and residential neighborhoods.

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_69f22488f224819081b0f3ec41ab975c completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68193b2b08190a00f08dbba490563 completed May 2, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7aeded27f88190a53f0bcd6ef78958 completed Aug. 11, 2026, 9:39 a.m.
NEDg Description generation batch_6a7aee8722b48190937dbed11e16272e completed Aug. 11, 2026, 9:42 a.m.
NED2 Entity disambiguation (via description) batch_6a7aeef6652c8190a528fe461a9a8382 completed Aug. 11, 2026, 9:44 a.m.
Created at: April 29, 2026, 7:51 p.m.