Triple

T599677
Position Surface form Disambiguated ID Type / Status
Subject Saxony E11465 entity
Predicate contains P35 FINISHED
Object Freiberg
Freiberg is a historic mining town in eastern Germany renowned for its silver mining heritage and well-preserved medieval architecture.
 E123043 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: Freiberg | Statement: [Saxony, contains, Freiberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Freiberg
Context triple: [Saxony, contains, Freiberg]
  • A. Zwickau
    Zwickau is a city in the German state of Saxony known historically as an important center of the automotive industry and as the birthplace of composer Robert Schumann.
  • B. Görlitz
    Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
  • C. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • D. Zwönitz
    Zwönitz is a river in Saxony, Germany, that serves as one of the headstreams of the Chemnitz River.
  • E. Pöcking
    Pöcking is a municipality in Bavaria, Germany, located on the western shore of Lake Starnberg and known for its affluent residential character.
  • 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: Freiberg
Triple: [Saxony, contains, Freiberg]
Generated description
Freiberg is a historic mining town in eastern Germany renowned for its silver mining heritage and well-preserved medieval architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Freiberg
Target entity description: Freiberg is a historic mining town in eastern Germany renowned for its silver mining heritage and well-preserved medieval architecture.
  • A. Zwickau
    Zwickau is a city in the German state of Saxony known historically as an important center of the automotive industry and as the birthplace of composer Robert Schumann.
  • B. Görlitz
    Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
  • C. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • D. Zwönitz
    Zwönitz is a river in Saxony, Germany, that serves as one of the headstreams of the Chemnitz River.
  • E. Pöcking
    Pöcking is a municipality in Bavaria, Germany, located on the western shore of Lake Starnberg and known for its affluent residential character.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d78c0f08190b83ad89062ccb0b9 completed March 1, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4279b23c8190854732f4d6d5d6cd completed March 7, 2026, 3:21 p.m.
NEDg Description generation batch_69ac430384ec8190a307c895bb12a122 completed March 7, 2026, 3:23 p.m.
NED2 Entity disambiguation (via description) batch_69ac437b62bc8190abfb721c570b4768 completed March 7, 2026, 3:25 p.m.
Created at: March 1, 2026, 7:35 p.m.