Triple

T2243234
Position Surface form Disambiguated ID Type / Status
Subject East Prussia E49443 entity
Predicate majorCity P316 FINISHED
Object Allenstein
Allenstein, now known as Olsztyn, is a historic city in northern Poland that once served as an important administrative and cultural center of East Prussia.
 E246982 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: Allenstein | Statement: [East Prussia, majorCity, Allenstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Allenstein
Context triple: [East Prussia, majorCity, Allenstein]
  • A. Ernst
    Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • B. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • C. Othmar
    Othmar is a masculine given name of Germanic origin, notably borne by the Swiss-American civil engineer Othmar Ammann.
  • D. Hermann Blankenstein
    Hermann Blankenstein was a prominent 19th-century German architect best known for designing numerous public buildings in Berlin, particularly schools and administrative structures.
  • E. Morgenstern
    Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
  • 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: Allenstein
Triple: [East Prussia, majorCity, Allenstein]
Generated description
Allenstein, now known as Olsztyn, is a historic city in northern Poland that once served as an important administrative and cultural center of East Prussia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Allenstein
Target entity description: Allenstein, now known as Olsztyn, is a historic city in northern Poland that once served as an important administrative and cultural center of East Prussia.
  • A. Ernst
    Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • B. Günther
    Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
  • C. Othmar
    Othmar is a masculine given name of Germanic origin, notably borne by the Swiss-American civil engineer Othmar Ammann.
  • D. Hermann Blankenstein
    Hermann Blankenstein was a prominent 19th-century German architect best known for designing numerous public buildings in Berlin, particularly schools and administrative structures.
  • E. Morgenstern
    Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
  • 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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0c157e88190a5bc876d9591a24b completed March 7, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b10c38c8190af7d6d99f9377df1 completed March 9, 2026, 6:39 a.m.
NEDg Description generation batch_69ae6bbdef14819084b96389435ca080 completed March 9, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_69ae6c2cfac48190b0425088e79cd122 completed March 9, 2026, 6:43 a.m.
Created at: March 4, 2026, 7:47 p.m.