Triple

T15968911
Position Surface form Disambiguated ID Type / Status
Subject Löhne E387268 entity
Predicate subdivision P747 FINISHED
Object Ulenburg
Ulenburg is a district or locality within the town of Löhne in North Rhine-Westphalia, Germany.
E1231699 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: Ulenburg | Statement: [Löhne, subdivision, Ulenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulenburg
Context triple: [Löhne, subdivision, Ulenburg]
  • A. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • B. Zhigulevsk
    Zhigulevsk is an industrial city in Russia located on the Volga River, known for its proximity to the Zhiguli Mountains and the Zhiguli Hydroelectric Station.
  • C. Sestroretsk
    Sestroretsk is a town in northwestern Russia, now part of Saint Petersburg, historically known for its arms factory and seaside resort area on the Gulf of Finland.
  • D. Kovrov
    Kovrov is an industrial city in western Russia known for its machine-building and arms manufacturing industries.
  • E. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • 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: Ulenburg
Triple: [Löhne, subdivision, Ulenburg]
Generated description
Ulenburg is a district or locality within the town of Löhne in North Rhine-Westphalia, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ulenburg
Target entity description: Ulenburg is a district or locality within the town of Löhne in North Rhine-Westphalia, Germany.
  • A. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • B. Zhigulevsk
    Zhigulevsk is an industrial city in Russia located on the Volga River, known for its proximity to the Zhiguli Mountains and the Zhiguli Hydroelectric Station.
  • C. Sestroretsk
    Sestroretsk is a town in northwestern Russia, now part of Saint Petersburg, historically known for its arms factory and seaside resort area on the Gulf of Finland.
  • D. Kovrov
    Kovrov is an industrial city in western Russia known for its machine-building and arms manufacturing industries.
  • E. Kirov
    Kirov is the revolutionary pseudonym of Sergei Kirov, a prominent early Soviet political leader and close associate of Joseph Stalin.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1572847f08190830e30125e829766 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a502c82881908d5b6f7c23e8a403 completed May 10, 2026, 3:32 p.m.
NEDg Description generation batch_6a00a5b3ce848190a73f06d9708bfc85 completed May 10, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_6a00a6734d008190bb0a5aa28826e73a completed May 10, 2026, 3:38 p.m.
Created at: April 10, 2026, 4:54 a.m.