Triple

T33153973
Position Surface form Disambiguated ID Type / Status
Subject Dorsten E848517 entity
Predicate hasMuseum P105 FINISHED
Object Jewish Museum of Westphalia
The Jewish Museum of Westphalia is a regional museum in Dorsten, Germany, dedicated to preserving and presenting the history and culture of Jewish life in Westphalia.
E2047468 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: Jewish Museum of Westphalia | Statement: [Dorsten, hasMuseum, Jewish Museum of Westphalia]
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: Jewish Museum of Westphalia
Triple: [Dorsten, hasMuseum, Jewish Museum of Westphalia]
Generated description
The Jewish Museum of Westphalia is a regional museum in Dorsten, Germany, dedicated to preserving and presenting the history and culture of Jewish life in Westphalia.

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_69f3495b02d08190bb3d366823dffc21 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d8dd0f708190a9f04f7b997b777c completed May 3, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3551e7eee48190991c82010faf8cbe completed June 19, 2026, 2:27 p.m.
NEDg Description generation batch_6a35550fa7e48190bd1b4c742b1f7c95 completed June 19, 2026, 2:41 p.m.
NED2 Entity disambiguation (via description) batch_6a3555725c7081908e8bb5012d737716 completed June 19, 2026, 2:42 p.m.
Created at: May 1, 2026, 1:28 a.m.