Triple

T17686831
Position Surface form Disambiguated ID Type / Status
Subject Hillerød Station E440913 entity
Predicate connectsTo P845 FINISHED
Object Gilleleje
Gilleleje is a coastal town and fishing port in northern Zealand, Denmark, known for its harbor, beaches, and maritime heritage.
 E1287575 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: Gilleleje | Statement: [Hillerød Station, connectsTo, Gilleleje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gilleleje
Context triple: [Hillerød Station, connectsTo, Gilleleje]
  • A. Grenaa
    Grenaa is a coastal town in eastern Jutland, Denmark, known for its ferry connections to the island of Anholt and its role as a regional commercial and educational center.
  • B. Farsø
    Farsø is a small Danish town in North Jutland, best known as the birthplace of Nobel Prize–winning author Johannes V. Jensen.
  • C. Lemvig
    Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
  • D. Faaborg
    Faaborg is a historic coastal town on the island of Funen in southern Denmark, known for its well-preserved old town, harbor, and cultural attractions.
  • E. Frederikshavn
    Frederikshavn is a port town in northern Jutland, Denmark, known for its ferry connections to Norway and Sweden and its maritime industry.
  • 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: Gilleleje
Triple: [Hillerød Station, connectsTo, Gilleleje]
Generated description
Gilleleje is a coastal town and fishing port in northern Zealand, Denmark, known for its harbor, beaches, and maritime heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gilleleje
Target entity description: Gilleleje is a coastal town and fishing port in northern Zealand, Denmark, known for its harbor, beaches, and maritime heritage.
  • A. Grenaa
    Grenaa is a coastal town in eastern Jutland, Denmark, known for its ferry connections to the island of Anholt and its role as a regional commercial and educational center.
  • B. Farsø
    Farsø is a small Danish town in North Jutland, best known as the birthplace of Nobel Prize–winning author Johannes V. Jensen.
  • C. Lemvig
    Lemvig is a small coastal town in western Denmark known for its harbor, hilly landscape, and location along the Limfjord.
  • D. Faaborg
    Faaborg is a historic coastal town on the island of Funen in southern Denmark, known for its well-preserved old town, harbor, and cultural attractions.
  • E. Frederikshavn
    Frederikshavn is a port town in northern Jutland, Denmark, known for its ferry connections to Norway and Sweden and its maritime industry.
  • 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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e470488c4081909b747313ef97b69c completed April 19, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02f82687b0819082ecb3cb9c883538 completed May 12, 2026, 9:51 a.m.
NEDg Description generation batch_6a02f8ba9f3c8190adf8ca9b8a7295a0 completed May 12, 2026, 9:54 a.m.
NED2 Entity disambiguation (via description) batch_6a02f97d8c9081908ecaba1ffdb07332 completed May 12, 2026, 9:57 a.m.
Created at: April 10, 2026, 10:03 a.m.