Triple

T31887574
Position Surface form Disambiguated ID Type / Status
Subject Municipality of Crowsnest Pass E814045 entity
Predicate hasSettlement P1068 FINISHED
Object Frank
Frank is a small historic community within the Municipality of Crowsnest Pass in southwestern Alberta, Canada, best known for the 1903 Frank Slide rock avalanche.
E1981585 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: Frank | Statement: [Municipality of Crowsnest Pass, hasSettlement, Frank]
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: Frank
Triple: [Municipality of Crowsnest Pass, hasSettlement, Frank]
Generated description
Frank is a small historic community within the Municipality of Crowsnest Pass in southwestern Alberta, Canada, best known for the 1903 Frank Slide rock avalanche.

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_69f348ef817481908440e2250319bcc8 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6b0e999888190b9dd00c81f5df261 completed May 3, 2026, 2:20 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e8a1cfd5c81908a9480238149a486 completed June 14, 2026, 11:01 a.m.
NEDg Description generation batch_6a2e8ad753688190829398ff32cf09e8 completed June 14, 2026, 11:04 a.m.
NED2 Entity disambiguation (via description) batch_6a2e8b9c48a48190a1c5bef0fe49f633 completed June 14, 2026, 11:08 a.m.
Created at: April 30, 2026, 11:57 p.m.