Triple

T10939429
Position Surface form Disambiguated ID Type / Status
Subject Marion Weiss E258425 entity
Predicate employer P7 FINISHED
Object Weiss/Manfredi E135761 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/Manfredi | Statement: [Marion Weiss, employer, Weiss/Manfredi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weiss/Manfredi
Context triple: [Marion Weiss, employer, Weiss/Manfredi]
  • A. Weiss/Manfredi chosen
    Weiss/Manfredi is a New York–based architecture and design firm known for its innovative, landscape-integrated cultural and institutional projects.
  • B. Weiss
    Weiss is a common German-language surname borne by numerous notable individuals across fields such as entertainment, science, and politics.
  • C. Weissman
    Weissman is a surname most prominently associated with Drew Weissman, the Nobel Prize–winning physician-scientist whose work on mRNA technology enabled the development of COVID-19 vaccines.
  • D. 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.
  • E. von Weichs
    von Weichs is a German noble family name most prominently associated with Maximilian von Weichs, a senior Wehrmacht field marshal during World War II.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c1389881909341170984211810 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d722972c8190b14637dc9e52ce11 completed April 18, 2026, 12:58 a.m.
Created at: April 8, 2026, 9:23 p.m.