Triple

T35195232
Position Surface form Disambiguated ID Type / Status
Subject Westerwald stoneware E1016237 entity
Predicate producedIn P3992 FINISHED
Object Siershahn
Siershahn is a municipality in western Germany known historically as a center of production for the region’s distinctive Westerwald stoneware ceramics.
E2234663 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: Siershahn | Statement: [Westerwald stoneware, producedIn, Siershahn]
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: Siershahn
Triple: [Westerwald stoneware, producedIn, Siershahn]
Generated description
Siershahn is a municipality in western Germany known historically as a center of production for the region’s distinctive Westerwald stoneware ceramics.

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_69f76dde814c8190a71f60d514a424a4 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78e308b408190afcb3f1de46c6187 completed May 3, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40a7d5cf7c8190858a864c14ebb2db completed June 28, 2026, 4:49 a.m.
NEDg Description generation batch_6a40a9675434819092d1606edfa90482 completed June 28, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_6a40a9ffe2688190ad8c76e103b9eace completed June 28, 2026, 4:58 a.m.
Created at: May 3, 2026, 4:02 p.m.