Triple

T22234028
Position Surface form Disambiguated ID Type / Status
Subject Haderslev Fjord E549540 entity
Predicate nearbySettlement P350 FINISHED
Object Hejsager
Hejsager is a small coastal settlement in southern Denmark situated near Haderslev Fjord, known for its beaches and scenic natural surroundings.
 E1525836 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: Hejsager | Statement: [Haderslev Fjord, nearbySettlement, Hejsager]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hejsager
Context triple: [Haderslev Fjord, nearbySettlement, Hejsager]
  • A. Alcochete
    Alcochete is a town in Portugal, near Lisbon on the south bank of the Tagus River, known historically as the birthplace of King Manuel I and for its traditional fishing and salt industries.
  • B. Hanna
    Hanna is the first name of Hanna Holborn Gray, a prominent American historian and former president of the University of Chicago.
  • C. Hanna
    Hanna is the petitioner in the U.S. Supreme Court case Hanna v. Plumer, which addressed the application of federal procedural rules in diversity jurisdiction cases.
  • D. Hanna
    Hanna was the wife of the influential 16th-century Jewish legal scholar and codifier Rabbi Joseph Karo.
  • E. Hanna
    "Hanna" is a 2011 action thriller film about a teenage girl trained as an assassin, known for its stylized direction and electronic score by The Chemical Brothers.
  • 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: Hejsager
Triple: [Haderslev Fjord, nearbySettlement, Hejsager]
Generated description
Hejsager is a small coastal settlement in southern Denmark situated near Haderslev Fjord, known for its beaches and scenic natural surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hejsager
Target entity description: Hejsager is a small coastal settlement in southern Denmark situated near Haderslev Fjord, known for its beaches and scenic natural surroundings.
  • A. Alcochete
    Alcochete is a town in Portugal, near Lisbon on the south bank of the Tagus River, known historically as the birthplace of King Manuel I and for its traditional fishing and salt industries.
  • B. Hanna
    Hanna is the first name of Hanna Holborn Gray, a prominent American historian and former president of the University of Chicago.
  • C. Hanna
    "Hanna" is a 2011 action thriller film about a teenage girl trained as an assassin, known for its stylized direction and electronic score by The Chemical Brothers.
  • D. Hanna
    Hanna is the petitioner in the U.S. Supreme Court case Hanna v. Plumer, which addressed the application of federal procedural rules in diversity jurisdiction cases.
  • E. Hanna
    Hanna was the wife of the influential 16th-century Jewish legal scholar and codifier Rabbi Joseph Karo.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf61504819093e70bee4c575d1c completed April 28, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0aae79b9bc819087fc52b30ad04781 completed May 18, 2026, 6:15 a.m.
NEDg Description generation batch_6a0ab00780f8819086ef4d3e5756133d completed May 18, 2026, 6:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0ab0befa5481909d00cb845dd67b12 completed May 18, 2026, 6:25 a.m.
Created at: April 16, 2026, 8:38 p.m.