Triple

T4250792
Position Surface form Disambiguated ID Type / Status
Subject Province of Posen E95844 entity
Predicate contains P35 FINISHED
Object Gnesen
Gnesen is a historic town in western Poland, known as one of the country’s earliest political and religious centers.
E424446 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: Gnesen | Statement: [Province of Posen, contains, Gnesen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gnesen
Context triple: [Province of Posen, contains, Gnesen]
  • A. Neefe
    Neefe is a German surname most notably associated with Christian Gottlob Neefe, an 18th-century composer and one of Beethoven’s early teachers.
  • B. Kremmen
    Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
  • C. Freyung
    Freyung is a small town in southeastern Bavaria, Germany, known as a gateway to the Bavarian Forest region.
  • D. Gantenbein
    Gantenbein is the enigmatic, shape-shifting central figure in Max Frisch’s novel "Mein Name sei Gantenbein," through whom themes of identity, role-playing, and the fluidity of self are explored.
  • E. Schöngarth
    Schöngarth is a German surname most notably associated with Eberhard Schöngarth, a high-ranking Nazi SS officer and war criminal during World War II.
  • 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: Gnesen
Triple: [Province of Posen, contains, Gnesen]
Generated description
Gnesen is a historic town in western Poland, known as one of the country’s earliest political and religious centers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gnesen
Target entity description: Gnesen is a historic town in western Poland, known as one of the country’s earliest political and religious centers.
  • A. Neefe
    Neefe is a German surname most notably associated with Christian Gottlob Neefe, an 18th-century composer and one of Beethoven’s early teachers.
  • B. Kremmen
    Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
  • C. Freyung
    Freyung is a small town in southeastern Bavaria, Germany, known as a gateway to the Bavarian Forest region.
  • D. Gantenbein
    Gantenbein is the enigmatic, shape-shifting central figure in Max Frisch’s novel "Mein Name sei Gantenbein," through whom themes of identity, role-playing, and the fluidity of self are explored.
  • E. Goppenstein
    Goppenstein is a small Swiss village in the canton of Valais, best known as a key railway junction and car shuttle station on the Lötschberg route through the Alps.
  • 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e9f11008190a0021e0ad730a79d completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a88225288190bb627de15da77c42 completed March 14, 2026, 6:27 p.m.
NEDg Description generation batch_69b5a959f3f08190af8b7b87afe15a54 completed March 14, 2026, 6:30 p.m.
NED2 Entity disambiguation (via description) batch_69b5ad13d2988190bc43050ac73919fa completed March 14, 2026, 6:46 p.m.
Created at: March 12, 2026, 11:06 p.m.