Triple

T27084890
Position Surface form Disambiguated ID Type / Status
Subject Emil Sick E686009 entity
Predicate founded P104 FINISHED
Object Sicks' Breweries Ltd.
Sicks' Breweries Ltd. was a prominent Canadian brewing company known for its regional beer production and association with entrepreneur Emil Sick, who also owned several sports franchises.
E1753941 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: Sicks' Breweries Ltd. | Statement: [Emil Sick, founded, Sicks' Breweries Ltd.]
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: Sicks' Breweries Ltd.
Triple: [Emil Sick, founded, Sicks' Breweries Ltd.]
Generated description
Sicks' Breweries Ltd. was a prominent Canadian brewing company known for its regional beer production and association with entrepreneur Emil Sick, who also owned several sports franchises.

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_69ef148940ec819097b5c20fbfbf7c81 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62345517c819082ca0c9f67792e67 completed May 2, 2026, 4:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123ae1f0448190a7294ccd37dd6a5d completed May 23, 2026, 11:40 p.m.
NEDg Description generation batch_6a123baa5c608190908cb92bee2e9cb2 completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123c6a4e4481908d79c547106ba5f0 completed May 23, 2026, 11:46 p.m.
Created at: April 27, 2026, 8:37 a.m.