Triple

T17419152
Position Surface form Disambiguated ID Type / Status
Subject Cameron Falls E423563 entity
Predicate watercourse P415 FINISHED
Object Cameron Creek
Cameron Creek is a stream in Waterton Lakes National Park in Alberta, Canada, known for feeding the scenic Cameron Falls.
E1828573 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: Cameron Creek | Statement: [Cameron Falls, watercourse, Cameron Creek]
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: Cameron Creek
Triple: [Cameron Falls, watercourse, Cameron Creek]
Generated description
Cameron Creek is a stream in Waterton Lakes National Park in Alberta, Canada, known for feeding the scenic Cameron Falls.

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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44234d840819096484a15d407785a completed April 19, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc34b59508190b1587ae59de04eef completed May 31, 2026, 11:24 p.m.
NEDg Description generation batch_6a1cc44ac1448190b0dc305eb5e460be completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc571b3b481908c523e5bad5e086a completed May 31, 2026, 11:34 p.m.
Created at: April 10, 2026, 5:46 a.m.