Triple

T489634
Position Surface form Disambiguated ID Type / Status
Subject Saar Offensive E9956 entity
Predicate location P40 FINISHED
Object Saar region E36080 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: Saar region | Statement: [Saar Offensive, location, Saar region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saar region
Context triple: [Saar Offensive, location, Saar region]
  • A. Saarland chosen
    Saarland is a small federal state in southwestern Germany known for its industrial history, Franco-German cultural influences, and location along the borders with France and Luxembourg.
  • B. Alsace-Lorraine
    Alsace-Lorraine is a historically contested border region between France and Germany, known for its mixed cultural heritage and strategic importance in European conflicts.
  • C. Rhineland
    The Rhineland is a historically significant region in western Germany along the Rhine River, long contested as a strategic and economic heartland in European conflicts.
  • D. Alsace
    Alsace is a historical and cultural region in northeastern France known for its blend of French and German influences, picturesque villages, and renowned wines.
  • E. Franconia
    Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
  • 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_69a2e802e2908190ab17c9479e0b6412 completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f0e0a9648190b6a3b2da3a3b51e6 completed Feb. 28, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4fc7b283c8190af5fb7fa649a9095 completed March 2, 2026, 2:56 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.