Triple

T22831116
Position Surface form Disambiguated ID Type / Status
Subject Calgary Dinos E565801 entity
Predicate notableAlumni P51 FINISHED
Object Erica Wiebe
Erica Wiebe is a Canadian freestyle wrestler and Olympic gold medallist known for winning the women’s 75 kg title at the 2016 Rio Games.
E1599540 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: Erica Wiebe | Statement: [Calgary Dinos, notableAlumni, Erica Wiebe]
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: Erica Wiebe
Triple: [Calgary Dinos, notableAlumni, Erica Wiebe]
Generated description
Erica Wiebe is a Canadian freestyle wrestler and Olympic gold medallist known for winning the women’s 75 kg title at the 2016 Rio Games.

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_69e24585ab1c81909b2b5065d15805d5 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17e2bcad8819091f237fd2273a20c completed April 29, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f5367bbe081909e422b884f67a59a completed May 21, 2026, 6:48 p.m.
NEDg Description generation batch_6a0f55d78200819088a55cdf614f4d76 completed May 21, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_6a0f569011808190ba60d79b533d8e56 completed May 21, 2026, 7:01 p.m.
Created at: April 17, 2026, 3:34 p.m.