Triple

T9182671
Position Surface form Disambiguated ID Type / Status
Subject Lolland E220370 entity
Predicate hasSettlement P1068 FINISHED
Object Rødby
Rødby is a small town on the Danish island of Lolland, known historically as a ferry port linking Denmark and Germany across the Baltic Sea.
 E826745 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: Rødby | Statement: [Lolland, hasSettlement, Rødby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rødby
Context triple: [Lolland, hasSettlement, Rødby]
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Blangsted
    Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • C. Rudkøbing
    Rudkøbing is a small historic town on the Danish island of Langeland, known for its well-preserved old streets and as the birthplace of physicist Hans Christian Ørsted.
  • D. Vækerø
    Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
  • E. Rønne
    Rønne is the largest town and administrative center of the Danish island of Bornholm, known for its historic harbor, half-timbered houses, and Baltic Sea ferry connections.
  • 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: Rødby
Triple: [Lolland, hasSettlement, Rødby]
Generated description
Rødby is a small town on the Danish island of Lolland, known historically as a ferry port linking Denmark and Germany across the Baltic Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rødby
Target entity description: Rødby is a small town on the Danish island of Lolland, known historically as a ferry port linking Denmark and Germany across the Baltic Sea.
  • A. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • B. Blangsted
    Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • C. Rudkøbing
    Rudkøbing is a small historic town on the Danish island of Langeland, known for its well-preserved old streets and as the birthplace of physicist Hans Christian Ørsted.
  • D. Vækerø
    Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
  • E. Rønne
    Rønne is the largest town and administrative center of the Danish island of Bornholm, known for its historic harbor, half-timbered houses, and Baltic Sea ferry connections.
  • 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_69ca83e589948190ac9907819db11ddf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccc2553e548190898434aeda517407 completed April 1, 2026, 6:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e3e1ac348190aec39a41b8b113dc completed April 5, 2026, 4:24 a.m.
NEDg Description generation batch_69d1e582a71c8190a7b67d37733db4aa completed April 5, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_69d1e617cdf88190bbc4cb733cbdd43b completed April 5, 2026, 4:33 a.m.
Created at: March 30, 2026, 7:23 p.m.