Triple

T14115820
Position Surface form Disambiguated ID Type / Status
Subject Peter Høj E339771 entity
Predicate familyName P18 FINISHED
Object Høj
Høj is a Danish surname most notably borne by Peter Høj, a prominent academic and university leader.
 E1079768 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: Høj | Statement: [Peter Høj, familyName, Høj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Høj
Context triple: [Peter Høj, familyName, Høj]
  • A. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • B. Højbro
    Højbro is a historic bridge in central Copenhagen that connects the islet of Slotsholmen with the rest of the city across the Inner Harbour.
  • C. Knudshoved
    Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
  • D. Vildbjerg
    Vildbjerg is a Danish town that serves as the administrative center of the former Trehøje Municipality in the Central Denmark Region.
  • E. Halsskov
    Halsskov is a district and ferry port in the Danish town of Korsør on the island of Zealand, known as the western landfall of the Great Belt Bridge.
  • 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: Høj
Triple: [Peter Høj, familyName, Høj]
Generated description
Høj is a Danish surname most notably borne by Peter Høj, a prominent academic and university leader.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Høj
Target entity description: Høj is a Danish surname most notably borne by Peter Høj, a prominent academic and university leader.
  • A. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • B. Højbro
    Højbro is a historic bridge in central Copenhagen that connects the islet of Slotsholmen with the rest of the city across the Inner Harbour.
  • C. Knudshoved
    Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
  • D. Vildbjerg
    Vildbjerg is a Danish town that serves as the administrative center of the former Trehøje Municipality in the Central Denmark Region.
  • E. Halsskov
    Halsskov is a district and ferry port in the Danish town of Korsør on the island of Zealand, known as the western landfall of the Great Belt Bridge.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6010a03c81909f5f160f8d1fa8fa completed April 14, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0baa328819099511dfa7b9666d3 completed May 7, 2026, 5:49 p.m.
NEDg Description generation batch_69fcd3a8b8e08190b230ab8a2215145e completed May 7, 2026, 6:02 p.m.
NED2 Entity disambiguation (via description) batch_69fcd48acddc819087d626c4764bf148 completed May 7, 2026, 6:06 p.m.
Created at: April 9, 2026, 10:22 p.m.