Triple

T27552204
Position Surface form Disambiguated ID Type / Status
Subject Budyšin E695533 entity
Predicate hasLandmark P105 FINISHED
Object Old Waterworks of Bautzen
The Old Waterworks of Bautzen is a historic water supply facility in the Saxon town of Bautzen, Germany, notable for its preserved medieval engineering and distinctive tower-like architecture along the Spree River.
 E1777694 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: Old Waterworks of Bautzen | Statement: [Budyšin, hasLandmark, Old Waterworks of Bautzen]
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: Old Waterworks of Bautzen
Triple: [Budyšin, hasLandmark, Old Waterworks of Bautzen]
Generated description
The Old Waterworks of Bautzen is a historic water supply facility in the Saxon town of Bautzen, Germany, notable for its preserved medieval engineering and distinctive tower-like architecture along the Spree River.

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_69ef5387e97c8190a9dab040d21cd048 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f8d77f48190b757e7afb1e7303b completed May 2, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c5c6a48c8190806aa0c850834de9 completed May 24, 2026, 9:32 a.m.
NEDg Description generation batch_6a12c6f592908190a6925a9c563dfdb0 completed May 24, 2026, 9:37 a.m.
NED2 Entity disambiguation (via description) batch_6a12c7a235f08190909cbd31986349d4 completed May 24, 2026, 9:40 a.m.
Created at: April 27, 2026, 1:35 p.m.