Triple

T7679174
Position Surface form Disambiguated ID Type / Status
Subject Compiègne E173943 entity
Predicate twinTown P1072 FINISHED
Object Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
E683488 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: Borghorst | Statement: [Compiègne, twinTown, Borghorst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borghorst
Context triple: [Compiègne, twinTown, Borghorst]
  • A. Glücksburg
    Glücksburg is a European royal house of German origin that has provided monarchs to several countries, including Denmark, Norway, and Greece.
  • B. Glücksburg
    Glücksburg is a small town in northern Germany known as the ancestral seat of the House of Schleswig-Holstein-Sonderburg-Glücksburg, a prominent European royal dynasty.
  • C. Havelberg
    Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
  • D. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • E. Teterow
    Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
  • 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: Borghorst
Triple: [Compiègne, twinTown, Borghorst]
Generated description
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Borghorst
Target entity description: Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
  • A. Glücksburg
    Glücksburg is a European royal house of German origin that has provided monarchs to several countries, including Denmark, Norway, and Greece.
  • B. Glücksburg
    Glücksburg is a small town in northern Germany known as the ancestral seat of the House of Schleswig-Holstein-Sonderburg-Glücksburg, a prominent European royal dynasty.
  • C. Havelberg
    Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
  • D. Osterburg
    Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
  • E. Teterow
    Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
  • 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_69c6995703e0819081de77361b602e78 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701fe2cc88190b5fd5e1378c32e5b completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8ac9af1c081908b0e100390258eaa completed March 29, 2026, 4:37 a.m.
NEDg Description generation batch_69c8af2fdd048190ad54dc9a4396d171 completed March 29, 2026, 4:48 a.m.
NED2 Entity disambiguation (via description) batch_69c8afe14810819094a236fb8f96e562 completed March 29, 2026, 4:51 a.m.
Created at: March 27, 2026, 4:01 p.m.