Triple

T20242214
Position Surface form Disambiguated ID Type / Status
Subject Cēsis E498325 entity
Predicate historicalName P65 FINISHED
Object Wenden E1130395 NE FINISHED

How this triple was built (2 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: Wenden | Statement: [Cēsis, historicalName, Wenden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wenden
Context triple: [Cēsis, historicalName, Wenden]
  • A. Wenden chosen
    Wenden was a historic town in present-day Latvia that served as a major political and administrative center of the Duchy of Livonia.
  • B. Wustrow
    Wustrow is a small town in the Wendland region of Lower Saxony, Germany, known for its rural character and traditional half-timbered architecture.
  • C. Retzow
    Retzow is a small municipality in the Havelland district of the federal state of Brandenburg in northeastern Germany.
  • D. Werneuchen
    Werneuchen is a small town in the German state of Brandenburg, located northeast of Berlin and characterized by its rural surroundings and commuter links to the capital.
  • E. Wrangelsburg
    Wrangelsburg is a historic estate and locality in northeastern Germany associated with the 17th-century Swedish field marshal and statesman Carl Gustaf Wrangel.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6716f9d248190a145f6883827ebbe completed April 20, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a084b9607b48190bc9c68c4e9b8f9b8 completed May 16, 2026, 10:48 a.m.
Created at: April 11, 2026, 11:40 p.m.