Triple

T28690878
Position Surface form Disambiguated ID Type / Status
Subject Füchschen brewery E729280 entity
Predicate hasProduct P3585 FINISHED
Object Füchschen Pils
Füchschen Pils is a German pilsner-style beer produced by the traditional Düsseldorf-based Füchschen brewery.
E1829601 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: Füchschen Pils | Statement: [Füchschen brewery, hasProduct, Füchschen Pils]
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: Füchschen Pils
Triple: [Füchschen brewery, hasProduct, Füchschen Pils]
Generated description
Füchschen Pils is a German pilsner-style beer produced by the traditional Düsseldorf-based Füchschen brewery.

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_69f043e60b6c8190ac2cd042e77fe6e9 completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f65685513481908f1f755464552fba completed May 2, 2026, 7:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cc3b235108190bdac7f5906d670df completed May 31, 2026, 11:26 p.m.
NEDg Description generation batch_6a1cc44b6ac081909cd782a2b589b6f5 completed May 31, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1cc544e60081908682c3750e6ac83d completed May 31, 2026, 11:33 p.m.
Created at: April 28, 2026, 5:36 a.m.