Triple

T10013957
Position Surface form Disambiguated ID Type / Status
Subject North Frisian Islands E199440 entity
Predicate hasIsland P970 FINISHED
Object Langeneß
Langeneß is a small Hallig island in the Wadden Sea off the coast of Schleswig-Holstein, Germany, known for its low-lying landscape, traditional Frisian culture, and vulnerability to tidal flooding.
E915739 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: Langeneß | Statement: [North Frisian Islands, hasIsland, Langeneß]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Langeneß
Context triple: [North Frisian Islands, hasIsland, Langeneß]
  • A. Lengenfeld
    Lengenfeld is a small town in the Free State of Saxony in eastern Germany, known as the birthplace of biblical scholar Constantin von Tischendorf.
  • B. Lahnstein
    Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
  • C. Röthlein
    Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
  • D. Lunzenau
    Lunzenau is a small town in the German state of Saxony, known for its location along the Zwickauer Mulde river and its historic architecture.
  • E. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
  • 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: Langeneß
Triple: [North Frisian Islands, hasIsland, Langeneß]
Generated description
Langeneß is a small Hallig island in the Wadden Sea off the coast of Schleswig-Holstein, Germany, known for its low-lying landscape, traditional Frisian culture, and vulnerability to tidal flooding.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Langeneß
Target entity description: Langeneß is a small Hallig island in the Wadden Sea off the coast of Schleswig-Holstein, Germany, known for its low-lying landscape, traditional Frisian culture, and vulnerability to tidal flooding.
  • A. Lengenfeld
    Lengenfeld is a small town in the Free State of Saxony in eastern Germany, known as the birthplace of biblical scholar Constantin von Tischendorf.
  • B. Lahnstein
    Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
  • C. Röthlein
    Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
  • D. Lunzenau
    Lunzenau is a small town in the German state of Saxony, known for its location along the Zwickauer Mulde river and its historic architecture.
  • E. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd3e35508190920468be167cb708 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4f31e3d5c8190a044eaf67ebc9f08 completed April 19, 2026, 3:22 p.m.
NEDg Description generation batch_69e4f7dbfafc8190afa1e9fe67f1296e completed April 19, 2026, 3:42 p.m.
NED2 Entity disambiguation (via description) batch_69e4ff4645948190a2bfcc3a4efd8e2a completed April 19, 2026, 4:13 p.m.
Created at: March 30, 2026, 8:52 p.m.