Triple

T27648931
Position Surface form Disambiguated ID Type / Status
Subject Racecourse Hill E696792 entity
Predicate associatedWith P37 FINISHED
Object High Street, Christchurch
High Street, Christchurch is a central thoroughfare in Christchurch, New Zealand, known for its historic streetscape, retail and hospitality venues, and role in the city’s post-earthquake redevelopment.
 E1784251 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: High Street, Christchurch | Statement: [Racecourse Hill, associatedWith, High Street, Christchurch]
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: High Street, Christchurch
Triple: [Racecourse Hill, associatedWith, High Street, Christchurch]
Generated description
High Street, Christchurch is a central thoroughfare in Christchurch, New Zealand, known for its historic streetscape, retail and hospitality venues, and role in the city’s post-earthquake redevelopment.

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_69ef590abd3c8190834d0193bde12007 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f631d34c388190bdeb6f523856fc33 completed May 2, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12da95dae48190b0144ef9d9f2367c completed May 24, 2026, 11:01 a.m.
NEDg Description generation batch_6a12db6f04608190aa0ee54293c46f57 completed May 24, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_6a12dcad965081909ea01fa8095164a6 completed May 24, 2026, 11:10 a.m.
Created at: April 27, 2026, 2:31 p.m.