Triple

T27291279
Position Surface form Disambiguated ID Type / Status
Subject Kings County, Nova Scotia E688632 entity
Predicate containsSettlement P847 FINISHED
Object Greenwood
Greenwood is a small Canadian community in Kings County, Nova Scotia, best known for its proximity to and association with the Royal Canadian Air Force base 14 Wing Greenwood.
E1563814 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: Greenwood | Statement: [Kings County, Nova Scotia, containsSettlement, Greenwood]
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: Greenwood
Triple: [Kings County, Nova Scotia, containsSettlement, Greenwood]
Generated description
Greenwood is a small Canadian community in Kings County, Nova Scotia, best known for its proximity to and association with the Royal Canadian Air Force base 14 Wing Greenwood.

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_69ef355a96308190a2bed991525fb278 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62759cb288190904e0b0531fea34d completed May 2, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12629e33e481908cd8ca7a38772943 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a126e52b7f48190a124771807a8f944 completed May 24, 2026, 3:19 a.m.
NED2 Entity disambiguation (via description) batch_6a126ecee1a08190b1a70b1f8514546f completed May 24, 2026, 3:21 a.m.
Created at: April 27, 2026, 11:15 a.m.