Triple

T8837293
Position Surface form Disambiguated ID Type / Status
Subject Drensteinfurt E210296 entity
Predicate hasPart P35 FINISHED
Object Walstedde
Walstedde is a village and district within the town of Drensteinfurt in North Rhine-Westphalia, Germany.
E761554 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: Walstedde | Statement: [Drensteinfurt, hasPart, Walstedde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walstedde
Context triple: [Drensteinfurt, hasPart, Walstedde]
  • A. Ramstedt
    Ramstedt is a Finnish surname most notably borne by linguist and diplomat Gustaf John Ramstedt, known for his pioneering work in Altaic and Mongolic studies.
  • B. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • C. Borghorst
    Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
  • D. Ballstad
    Ballstad is a fishing village in Norway’s Lofoten archipelago, known for its scenic coastal landscape and traditional maritime culture.
  • E. Hodenhagen
    Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
  • 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: Walstedde
Triple: [Drensteinfurt, hasPart, Walstedde]
Generated description
Walstedde is a village and district within the town of Drensteinfurt in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Walstedde
Target entity description: Walstedde is a village and district within the town of Drensteinfurt in North Rhine-Westphalia, Germany.
  • A. Ramstedt
    Ramstedt is a Finnish surname most notably borne by linguist and diplomat Gustaf John Ramstedt, known for his pioneering work in Altaic and Mongolic studies.
  • B. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • C. Borghorst
    Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
  • D. Ballstad
    Ballstad is a fishing village in Norway’s Lofoten archipelago, known for its scenic coastal landscape and traditional maritime culture.
  • E. Hodenhagen
    Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
  • 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_69ca8388549c819095fd94eadefbb007 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc606adde08190825dbdabd199c025 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf898a478c81908f138a78f331b87d completed April 3, 2026, 9:34 a.m.
NEDg Description generation batch_69cf8d66cb5081908efaa1d96829ebe8 completed April 3, 2026, 9:50 a.m.
NED2 Entity disambiguation (via description) batch_69cf8defb0508190b2341ba8e79da2af completed April 3, 2026, 9:52 a.m.
Created at: March 30, 2026, 6:48 p.m.