Triple

T1320710
Position Surface form Disambiguated ID Type / Status
Subject Oder River E28210 entity
Predicate majorCityOnRiver P316 FINISHED
Object Eisenhüttenstadt
Eisenhüttenstadt is an industrial planned city in eastern Germany, known for its large steelworks and postwar socialist urban design.
 E277662 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: Eisenhüttenstadt | Statement: [Oder River, majorCityOnRiver, Eisenhüttenstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Eisenhüttenstadt
Context triple: [Oder River, majorCityOnRiver, Eisenhüttenstadt]
  • A. Cottbus
    Cottbus is a city in eastern Germany known as a regional center for science and technology, including aerospace research.
  • B. 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.
  • C. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • D. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • E. Lichterfelde
    Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent 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: Eisenhüttenstadt
Triple: [Oder River, majorCityOnRiver, Eisenhüttenstadt]
Generated description
Eisenhüttenstadt is an industrial planned city in eastern Germany, known for its large steelworks and postwar socialist urban design.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Eisenhüttenstadt
Target entity description: Eisenhüttenstadt is an industrial planned city in eastern Germany, known for its large steelworks and postwar socialist urban design.
  • A. Cottbus
    Cottbus is a city in eastern Germany known as a regional center for science and technology, including aerospace research.
  • B. 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.
  • C. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • D. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • E. Lichterfelde
    Lichterfelde is a residential district in southwestern Berlin known for its historic villas, leafy streets, and affluent 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c179883c8190b68fbeebb9696982 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69af5ca0ede48190b2c45761a3f92517 completed March 9, 2026, 11:49 p.m.
NEDg Description generation batch_69af5f3ca94c8190a316b507dcec4599 completed March 10, 2026, 12:01 a.m.
NED2 Entity disambiguation (via description) batch_69af5fa4d13481908d0dac97dff14cc4 completed March 10, 2026, 12:02 a.m.
Created at: March 1, 2026, 7:55 p.m.