Triple

T14481723
Position Surface form Disambiguated ID Type / Status
Subject Walser E359116 entity
Predicate hasSubgroup P747 FINISHED
Object Issime Walser E359116 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: Issime Walser | Statement: [Walser, hasSubgroup, Issime Walser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Issime Walser
Context triple: [Walser, hasSubgroup, Issime Walser]
  • A. Walter Ullmann
    Walter Ullmann was a prominent 20th-century historian of medieval political thought, known for his influential studies on papal authority, legal theory, and the development of medieval political ideas.
  • B. Walser chosen
    Walser are a German-speaking Alpine people known for their distinctive culture, architecture, and dialects spread across high mountain communities in Switzerland and northern Italy.
  • C. Walter Süskindbrug
    Walter Süskindbrug is a historic canal bridge in Amsterdam named after Holocaust rescuer Walter Süskind.
  • D. Manuel Klein
    Manuel Klein was a German-born American actor and playwright active in the late 19th and early 20th centuries.
  • E. Robert Walser
    Robert Walser was a Swiss modernist writer known for his delicate, introspective prose and innovative short forms that deeply influenced later 20th-century literature and art.
  • 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924bc548819087a2f693840d7426 completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd64a41a8c819081a3eaabbe66577a completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:20 a.m.