Triple

T35028992
Position Surface form Disambiguated ID Type / Status
Subject Bad Düben E1010422 entity
Predicate hasLandmark P105 FINISHED
Object Stadtkirche St. Nikolai Bad Düben
Stadtkirche St. Nikolai Bad Düben is a historic Protestant town church in Bad Düben, Germany, notable for its traditional architecture and local religious significance.
E2122936 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: Stadtkirche St. Nikolai Bad Düben | Statement: [Bad Düben, hasLandmark, Stadtkirche St. Nikolai Bad Düben]
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: Stadtkirche St. Nikolai Bad Düben
Triple: [Bad Düben, hasLandmark, Stadtkirche St. Nikolai Bad Düben]
Generated description
Stadtkirche St. Nikolai Bad Düben is a historic Protestant town church in Bad Düben, Germany, notable for its traditional architecture and local religious significance.

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_69f76dccf0108190af43b465d3750196 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7854569208190a5c3bd8e5f8a8ea3 completed May 3, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37bd272e5c819090dd24e785ebf745 completed June 21, 2026, 10:29 a.m.
NEDg Description generation batch_6a37bda6c4408190a6f09442687dae28 completed June 21, 2026, 10:32 a.m.
NED2 Entity disambiguation (via description) batch_6a37bf374b7081908687f2997935411e completed June 21, 2026, 10:38 a.m.
Created at: May 3, 2026, 4:01 p.m.