Triple

T65477
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Medicine, University of Göttingen E1303 entity
Predicate funding P59 FINISHED
Object publicly funded LITERAL 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: publicly funded | Statement: [Faculty of Medicine, University of Göttingen, funding, publicly funded]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: funding
Context triple: [Faculty of Medicine, University of Göttingen, funding, publicly funded]
  • A. funds
    Indicates that one entity provides financial resources or monetary support to another entity or activity.
  • B. fundedBy
    Indicates that an entity receives financial support or resources from another entity.
  • C. fundingModel chosen
    Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
  • D. endowment
    Indicates that a resource, asset, or benefit is provided or allocated to an entity, typically as a lasting or dedicated funding source.
  • E. capital
    Indicates that one place serves as the official seat of government or primary administrative center for another political entity.
  • F. None of above.

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_69a24ba4f760819081f6638a3c70538a completed Feb. 28, 2026, 1:57 a.m.
NER Named-entity recognition batch_69a2516eda54819090f5c14384d4eab1 completed Feb. 28, 2026, 2:22 a.m.
PD Predicate disambiguation batch_69a24ea5c140819080409a968c8d2ce8 completed Feb. 28, 2026, 2:10 a.m.
Created at: Feb. 28, 2026, 2:02 a.m.