Triple

T1074716
Position Surface form Disambiguated ID Type / Status
Subject Rügen E23809 entity
Predicate hasTown P847 FINISHED
Object Göhren
Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
E196316 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: Göhren | Statement: [Rügen, hasTown, Göhren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Göhren
Context triple: [Rügen, hasTown, Göhren]
  • A. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • B. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • C. Ennigerloh
    Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
  • D. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • E. Walsrode
    Walsrode is a small town in Lower Saxony, Germany, known for its location in the Lüneburg Heath region and its large bird park, the Weltvogelpark Walsrode.
  • 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: Göhren
Triple: [Rügen, hasTown, Göhren]
Generated description
Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Göhren
Target entity description: Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
  • A. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • B. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • C. Ennigerloh
    Ennigerloh is a small town in the German state of North Rhine-Westphalia, known as the birthplace of mathematician Karl Weierstrass.
  • D. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • E. Walsrode
    Walsrode is a small town in Lower Saxony, Germany, known for its location in the Lüneburg Heath region and its large bird park, the Weltvogelpark Walsrode.
  • 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_69a493f1ddf48190a99d54b00e99f8ce completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b92cbfd481909e2f928c1d06ebaa completed March 1, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69ada0b527dc819085f7b3ff85170e16 completed March 8, 2026, 4:15 p.m.
NEDg Description generation batch_69ada1e13d408190b393c00c331125a2 completed March 8, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69ada292a34c8190a566c2909342ab27 completed March 8, 2026, 4:23 p.m.
Created at: March 1, 2026, 7:42 p.m.