Triple

T31830241
Position Surface form Disambiguated ID Type / Status
Subject Customs Street E812508 entity
Predicate hasNearbyLandmark P2064 FINISHED
Object Queen Street Valley
Queen Street Valley is an area in central Auckland, New Zealand, characterized by its urban streetscape, commercial activity, and proximity to the city’s waterfront and downtown core.
 E1980848 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: Queen Street Valley | Statement: [Customs Street, hasNearbyLandmark, Queen Street Valley]
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: Queen Street Valley
Triple: [Customs Street, hasNearbyLandmark, Queen Street Valley]
Generated description
Queen Street Valley is an area in central Auckland, New Zealand, characterized by its urban streetscape, commercial activity, and proximity to the city’s waterfront and downtown core.

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_6a2e65a0ce408190862bb30a13b77ca7 completed June 14, 2026, 8:26 a.m.
NEDg Description generation batch_6a2e742231e481908a826ba4996c0ee5 completed June 14, 2026, 9:28 a.m.
NED2 Entity disambiguation (via description) batch_6a2e755d0ff88190a05c3a77989b312e completed June 14, 2026, 9:33 a.m.
Created at: April 30, 2026, 11:47 p.m.