Triple

T23207496
Position Surface form Disambiguated ID Type / Status
Subject Rona Ambrose E580499 entity
Predicate representedArea P12167 FINISHED
Object Edmonton–Spruce Grove
Edmonton–Spruce Grove was a federal electoral district in Alberta, Canada, encompassing parts of the city of Edmonton and the nearby community of Spruce Grove.
E1607659 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: Edmonton–Spruce Grove | Statement: [Rona Ambrose, representedArea, Edmonton–Spruce Grove]
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: Edmonton–Spruce Grove
Triple: [Rona Ambrose, representedArea, Edmonton–Spruce Grove]
Generated description
Edmonton–Spruce Grove was a federal electoral district in Alberta, Canada, encompassing parts of the city of Edmonton and the nearby community of Spruce Grove.

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_69e24602ae1481908aaa6bc7ca493867 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1907d8be08190a100d99efaff9964 completed April 29, 2026, 5 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f75e5abc48190ab4fc496446a6f26 completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f77372e188190bbf5c1a77de0833c completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f77d47ea08190828e5f5f9f0e3899 completed May 21, 2026, 9:23 p.m.
Created at: April 17, 2026, 4:07 p.m.