Triple

T35481535
Position Surface form Disambiguated ID Type / Status
Subject Parksville region E1025483 entity
Predicate hasCommunity P2605 FINISHED
Object French Creek
French Creek is a small coastal community on Vancouver Island in British Columbia, known for its marina, fishing, and proximity to the cities of Parksville and Qualicum Beach.
E2189668 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: French Creek | Statement: [Parksville region, hasCommunity, French 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: French Creek
Triple: [Parksville region, hasCommunity, French Creek]
Generated description
French Creek is a small coastal community on Vancouver Island in British Columbia, known for its marina, fishing, and proximity to the cities of Parksville and Qualicum Beach.

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_69f76dfadba0819083456aadcd6864ea completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f796ed016481908cf401a288d0d5e2 completed May 3, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6bc2cd08190aef7e2e35316a8e0 completed June 23, 2026, 1:51 a.m.
NEDg Description generation batch_6a39eb96fa2081909dc4790068e70df1 completed June 23, 2026, 2:12 a.m.
NED2 Entity disambiguation (via description) batch_6a39ef75b4108190a21eae0fd8d705e8 completed June 23, 2026, 2:29 a.m.
Created at: May 3, 2026, 4:04 p.m.