Triple

T2049926
Position Surface form Disambiguated ID Type / Status
Subject Schleswig-Holstein E45540 entity
Predicate containsPeninsula P16192 FINISHED
Object Eiderstedt
Eiderstedt is a low-lying peninsula on Germany’s North Sea coast known for its dike-protected marshlands, agriculture, and coastal tourism.
E231954 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: Eiderstedt | Statement: [Schleswig-Holstein, containsPeninsula, Eiderstedt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eiderstedt
Context triple: [Schleswig-Holstein, containsPeninsula, Eiderstedt]
  • A. Hedesunda
    Hedesunda is a small locality in east-central Sweden known for its rural character and proximity to forests, lakes, and the Dalälven River.
  • B. Bojnord
    Bojnord is a city in northeastern Iran that serves as the capital of North Khorasan Province.
  • C. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • D. Hvalsey
    Hvalsey is the best-preserved Norse ruin site in Greenland, known for its stone church and remnants of a medieval farming settlement.
  • E. Grimstad
    Grimstad is a coastal town and municipality in southern Norway known for its maritime heritage, charming wooden houses, and role as a summer tourist destination.
  • 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: Eiderstedt
Triple: [Schleswig-Holstein, containsPeninsula, Eiderstedt]
Generated description
Eiderstedt is a low-lying peninsula on Germany’s North Sea coast known for its dike-protected marshlands, agriculture, and coastal tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Eiderstedt
Target entity description: Eiderstedt is a low-lying peninsula on Germany’s North Sea coast known for its dike-protected marshlands, agriculture, and coastal tourism.
  • A. Hedesunda
    Hedesunda is a small locality in east-central Sweden known for its rural character and proximity to forests, lakes, and the Dalälven River.
  • B. Bojnord
    Bojnord is a city in northeastern Iran that serves as the capital of North Khorasan Province.
  • C. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • D. Hvalsey
    Hvalsey is the best-preserved Norse ruin site in Greenland, known for its stone church and remnants of a medieval farming settlement.
  • E. Grimstad
    Grimstad is a coastal town and municipality in southern Norway known for its maritime heritage, charming wooden houses, and role as a summer tourist destination.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb98e10d48190bb96cd1f8ea3c08b completed March 7, 2026, 5:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae27170870819083112aee662c681c completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae29ee1db88190b137cf3840cb1146 completed March 9, 2026, 2:01 a.m.
NED2 Entity disambiguation (via description) batch_69ae2a3bd7c08190898c7a7627cabf2b completed March 9, 2026, 2:02 a.m.
Created at: March 4, 2026, 7:39 p.m.