Triple

T32005987
Position Surface form Disambiguated ID Type / Status
Subject Don Valley Brick Works E817268 entity
Predicate ownedBy P347 FINISHED
Object Evergreen (non-profit organization)
Evergreen is a Canadian environmental non-profit organization dedicated to creating sustainable, livable cities through urban greening, community engagement, and adaptive reuse of public spaces.
E1987906 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: Evergreen (non-profit organization) | Statement: [Don Valley Brick Works, ownedBy, Evergreen (non-profit organization)]
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: Evergreen (non-profit organization)
Triple: [Don Valley Brick Works, ownedBy, Evergreen (non-profit organization)]
Generated description
Evergreen is a Canadian environmental non-profit organization dedicated to creating sustainable, livable cities through urban greening, community engagement, and adaptive reuse of public spaces.

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_69f348f8ce388190ae84376b1f348f12 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b40069088190b352c80db1417268 completed May 3, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eb16575808190a2a370b3b64c9167 completed June 14, 2026, 1:49 p.m.
NEDg Description generation batch_6a2eb432d7ac8190859f0d7d201fde56 completed June 14, 2026, 2:01 p.m.
NED2 Entity disambiguation (via description) batch_6a2ece4cd5ec819094313a3c6cead279 completed June 14, 2026, 3:52 p.m.
Created at: May 1, 2026, 12:15 a.m.