Triple
T19884691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heinz Hartmann |
E477865
|
entity |
| Predicate | educatedAt |
P5
|
FINISHED |
| Object | Medical University of Vienna |
—
|
NE NERFINISHED |
How this triple was built (3 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: Medical University of Vienna | Statement: [Heinz Hartmann, educatedAt, Medical University of Vienna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Medical University of Vienna Context triple: [Heinz Hartmann, educatedAt, Medical University of Vienna]
-
A.
Medical University of Innsbruck
The Medical University of Innsbruck is a prominent Austrian institution specializing in medical education and research, located in the city of Innsbruck in Tyrol.
-
B.
Medical University of Graz
The Medical University of Graz is a public medical university in Graz, Austria, known for its research and education in medicine and health sciences.
-
C.
University of Vienna
The University of Vienna is one of Europe's oldest and largest universities, renowned for its contributions to the humanities and sciences since its founding in 1365.
-
D.
University of Innsbruck
The University of Innsbruck is a major Austrian public research university located in the city of Innsbruck, known for its strong programs across the sciences and humanities and its Alpine setting.
-
E.
Allgemeines Krankenhaus der Stadt Wien
Allgemeines Krankenhaus der Stadt Wien was the historic main general hospital of Vienna, renowned as a major center of medical treatment, teaching, and research.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Medical University of Vienna Target entity description: The Medical University of Vienna is a leading Austrian medical school and research institution renowned for its contributions to clinical medicine and biomedical science.
-
A.
Medical University of Innsbruck
The Medical University of Innsbruck is a prominent Austrian institution specializing in medical education and research, located in the city of Innsbruck in Tyrol.
-
B.
Medical University of Graz
The Medical University of Graz is a public medical university in Graz, Austria, known for its research and education in medicine and health sciences.
-
C.
University of Vienna
The University of Vienna is one of Europe's oldest and largest universities, renowned for its contributions to the humanities and sciences since its founding in 1365.
-
D.
University of Innsbruck
The University of Innsbruck is a major Austrian public research university located in the city of Innsbruck, known for its strong programs across the sciences and humanities and its Alpine setting.
-
E.
Allgemeines Krankenhaus der Stadt Wien
Allgemeines Krankenhaus der Stadt Wien was the historic main general hospital of Vienna, renowned as a major center of medical treatment, teaching, and research.
- F. None of above. chosen
Provenance (2 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659093df081909d3be9c3caeb79ba |
completed | April 20, 2026, 4:49 p.m. |
Created at: April 10, 2026, 1:52 p.m.