Triple

T31830227
Position Surface form Disambiguated ID Type / Status
Subject Customs Street E812508 entity
Predicate intersects P1018 FINISHED
Object Hobson Street
Hobson Street is a major thoroughfare in central Auckland, New Zealand, known for its commercial buildings, hotels, and proximity to the city’s waterfront and entertainment districts.
 E2290919 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: Hobson Street | Statement: [Customs Street, intersects, Hobson 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: Hobson Street
Triple: [Customs Street, intersects, Hobson Street]
Generated description
Hobson Street is a major thoroughfare in central Auckland, New Zealand, known for its commercial buildings, hotels, and proximity to the city’s waterfront and entertainment districts.

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_69f348ea7ffc8190a2ab43d80277cf59 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6af88728c8190b9aee1e8269369f1 completed May 3, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5c0f6e20748190a4efa4f7a726bacf completed July 18, 2026, 11:42 p.m.
NEDg Description generation batch_6a5c107975d88190bb58cb4b224aff53 completed July 18, 2026, 11:47 p.m.
NED2 Entity disambiguation (via description) batch_6a5c1107d19c819080568f9c275123e0 completed July 18, 2026, 11:49 p.m.
Created at: April 30, 2026, 11:47 p.m.