Triple

T14739637
Position Surface form Disambiguated ID Type / Status
Subject Rudolf Weiss E346308 entity
Predicate hasSurname P18 FINISHED
Object Weiss E68163 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: Weiss | Statement: [Rudolf Weiss, hasSurname, Weiss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weiss
Context triple: [Rudolf Weiss, hasSurname, Weiss]
  • A. Weiss chosen
    Weiss is a common German-language surname borne by numerous notable individuals across fields such as entertainment, science, and politics.
  • B. Weiss/Manfredi
    Weiss/Manfredi is a New York–based architecture and design firm known for its innovative, landscape-integrated cultural and institutional projects.
  • C. Bianco
    Bianco is an Italian surname commonly associated with individuals of Italian heritage, including the artist Enrico Bianco.
  • D. Branca
    Branca is a surname most notably associated with former Major League Baseball pitcher Ralph Branca.
  • E. Weis
    Weis is a surname most prominently associated with Charlie Weis, an American football coach known for his tenure with the Notre Dame Fighting Irish and in the NFL.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7345680819093e901233a064e48 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb91fdf88190bdcc9a93289f6b7f completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:29 a.m.