Triple

T11792304
Position Surface form Disambiguated ID Type / Status
Subject Prince of Salm-Kyrburg E280417 entity
Predicate associatedWithRegion P285 FINISHED
Object Rhineland E60266 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: Rhineland | Statement: [Prince of Salm-Kyrburg, associatedWithRegion, Rhineland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rhineland
Context triple: [Prince of Salm-Kyrburg, associatedWithRegion, Rhineland]
  • A. Rhineland chosen
    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.
  • B. Rijnland
    Rijnland is a historical region in the western Netherlands, centered around the lower Rhine delta and known for its extensive water management and polder landscapes.
  • C. Rhine-Weser region
    The Rhine-Weser region is a historical area in western Germany associated with the early homeland and formation of the Frankish people.
  • D. Westphalia
    Westphalia is a historical region in northwestern Germany known for being the site of the 1648 treaties that ended the Thirty Years' War and reshaped the political order of Europe.
  • E. Siegerland
    Siegerland is a hilly, forested region in western Germany known for its historic iron ore mining and metalworking industry.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a588d2c881909783c2d678c2a474 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f280fe1b2881908c32b920cdaf04df completed April 29, 2026, 10:06 p.m.
Created at: April 8, 2026, 9:42 p.m.