Triple

T9190025
Position Surface form Disambiguated ID Type / Status
Subject Wielbark E220557 entity
Predicate historicalName P65 FINISHED
Object Willenberg
Willenberg is the former German name of the town now known as Wielbark, located in northern Poland.
 E788133 NE FINISHED

How this triple was built (4 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: Willenberg | Statement: [Wielbark, historicalName, Willenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Willenberg
Context triple: [Wielbark, historicalName, Willenberg]
  • A. Wurmberg
    Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
  • B. Widdersberg
    Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
  • C. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • D. Waidberg
    Waidberg is a wooded hill and recreational area on the outskirts of Zurich, Switzerland, known for its hiking trails, viewpoints, and proximity to the Hönggerberg.
  • E. Hornsberg
    Hornsberg is a waterfront residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Willenberg
Triple: [Wielbark, historicalName, Willenberg]
Generated description
Willenberg is the former German name of the town now known as Wielbark, located in northern Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Willenberg
Target entity description: Willenberg is the former German name of the town now known as Wielbark, located in northern Poland.
  • A. Wurmberg
    Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
  • B. Widdersberg
    Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
  • C. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • D. Waidberg
    Waidberg is a wooded hill and recreational area on the outskirts of Zurich, Switzerland, known for its hiking trails, viewpoints, and proximity to the Hönggerberg.
  • E. Hornsberg
    Hornsberg is a waterfront residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
  • F. None of above. chosen

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_69ca83e6d77c81909862b7afef56b1bf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd5bd8c5c81909d0cdbcd7410fcee completed April 1, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09b8b37488190b72f2b4c55fd9a8c completed April 4, 2026, 5:03 a.m.
NEDg Description generation batch_69d09cf11e488190b61f4a61002454e6 completed April 4, 2026, 5:09 a.m.
NED2 Entity disambiguation (via description) batch_69d09e2069048190ac22b738fa324771 completed April 4, 2026, 5:14 a.m.
Created at: March 30, 2026, 7:24 p.m.