Triple

T22740872
Position Surface form Disambiguated ID Type / Status
Subject Haderslev Municipality E562407 entity
Predicate contains P35 FINISHED
Object Hejsager NE NERFINISHED

How this triple was built (2 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 Municipality, contains, Hejsager]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hejsager
Context triple: [Haderslev Municipality, contains, Hejsager]
  • A. Hejsager chosen
    Hejsager is a small coastal settlement in southern Denmark situated near Haderslev Fjord, known for its beaches and scenic natural surroundings.
  • B. 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.
  • C. Hanna
    Hanna is the first name of Hanna Holborn Gray, a prominent American historian and former president of the University of Chicago.
  • 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" 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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17972fde8819086094cea289a2af8 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:23 p.m.