Triple

T2777530
Position Surface form Disambiguated ID Type / Status
Subject Göttingen district E61609 entity
Predicate contains P35 FINISHED
Object Friedland
Friedland is a municipality in Lower Saxony, Germany, known for its historic border location and post-World War II refugee transit camp.
 E296394 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: Friedland | Statement: [Göttingen district, contains, Friedland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Friedland
Context triple: [Göttingen district, contains, Friedland]
  • A. Friedland
    Friedland is a town in present-day Pravdinsk, Russia, historically notable as the site of the decisive 1807 Napoleonic battle between French and Russian forces.
  • B. Biebrich
    Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
  • C. Borsigwalde
    Borsigwalde is a residential locality in the Berlin borough of Reinickendorf, known for its industrial heritage linked to the Borsig engineering works.
  • D. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • E. Elbing
    Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
  • 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: Friedland
Triple: [Göttingen district, contains, Friedland]
Generated description
Friedland is a municipality in Lower Saxony, Germany, known for its historic border location and post-World War II refugee transit camp.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Friedland
Target entity description: Friedland is a municipality in Lower Saxony, Germany, known for its historic border location and post-World War II refugee transit camp.
  • A. Friedland
    Friedland is a town in present-day Pravdinsk, Russia, historically notable as the site of the decisive 1807 Napoleonic battle between French and Russian forces.
  • B. Biebrich
    Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
  • C. Borsigwalde
    Borsigwalde is a residential locality in the Berlin borough of Reinickendorf, known for its industrial heritage linked to the Borsig engineering works.
  • D. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • E. Elbing
    Elbing is a historic Baltic port city, now known as Elbląg in Poland, that played a notable role in medieval trade as part of the Hanseatic commercial network.
  • 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_69ab4b7e43c48190997b8fc8fb1663ab completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd82a864819082bd1181a16d5208 completed March 7, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc05adf908190bd16bbb6f8ea213a completed March 10, 2026, 6:55 a.m.
NEDg Description generation batch_69afc0d32d5881908b80e0bfca5cd873 completed March 10, 2026, 6:57 a.m.
NED2 Entity disambiguation (via description) batch_69afc13548088190a2d5f48144c853a4 completed March 10, 2026, 6:59 a.m.
Created at: March 6, 2026, 9:57 p.m.