Triple
T85917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany |
E1728
|
entity |
| Predicate | hasNotableUniversity |
P315
|
FINISHED |
| Object |
Ludwig Maximilian University of Munich
Ludwig Maximilian University of Munich is one of Germany’s oldest and most prestigious research universities, renowned for its strong academic programs and influential contributions across the sciences and humanities.
|
E23761
|
NE FINISHED |
How this triple was built (5 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: Ludwig Maximilian University of Munich | Statement: [Germany, hasNotableUniversity, Ludwig Maximilian University of Munich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludwig Maximilian University of Munich Context triple: [Germany, hasNotableUniversity, Ludwig Maximilian University of Munich]
-
A.
Humboldt University of Berlin
Humboldt University of Berlin is a prestigious public research university in Germany’s capital, renowned for its historic contributions to science and the humanities and for pioneering the modern research university model.
-
B.
University of Leipzig
The University of Leipzig is one of Germany’s oldest and most prestigious universities, renowned for its contributions to research and education in the humanities, natural sciences, and social sciences.
-
C.
University of Göttingen
The University of Göttingen is a renowned German research university, historically significant in physics and mathematics and once a leading center for theoretical science in Europe.
-
D.
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.
-
E.
University of Zurich
The University of Zurich is a major public research university in Switzerland renowned for its contributions to science and scholarship, including being one of the institutions where Albert Einstein taught.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ludwig Maximilian University of Munich Triple: [Germany, hasNotableUniversity, Ludwig Maximilian University of Munich]
Generated description
Ludwig Maximilian University of Munich is one of Germany’s oldest and most prestigious research universities, renowned for its strong academic programs and influential contributions across the sciences and humanities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ludwig Maximilian University of Munich Target entity description: Ludwig Maximilian University of Munich is one of Germany’s oldest and most prestigious research universities, renowned for its strong academic programs and influential contributions across the sciences and humanities.
-
A.
Humboldt University of Berlin
Humboldt University of Berlin is a prestigious public research university in Germany’s capital, renowned for its historic contributions to science and the humanities and for pioneering the modern research university model.
-
B.
University of Leipzig
The University of Leipzig is one of Germany’s oldest and most prestigious universities, renowned for its contributions to research and education in the humanities, natural sciences, and social sciences.
-
C.
University of Göttingen
The University of Göttingen is a renowned German research university, historically significant in physics and mathematics and once a leading center for theoretical science in Europe.
-
D.
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.
-
E.
University of Zurich
The University of Zurich is a major public research university in Switzerland renowned for its contributions to science and scholarship, including being one of the institutions where Albert Einstein taught.
- F. None of above. chosen
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableUniversity Context triple: [Germany, hasNotableUniversity, Ludwig Maximilian University of Munich]
-
A.
hasPublicUniversityCampus
Indicates that a public university maintains or operates a campus at the specified location.
-
B.
hasMajorUniversity
chosen
Indicates that a location or region contains at least one prominent, large, or academically significant university.
-
C.
hasMainCampus
Indicates that an educational institution is primarily based at or chiefly associated with a particular campus location.
-
D.
includesPublicUniversities
Indicates that the subject set or collection contains one or more public universities as members.
-
E.
hasDoctoralPrograms
Indicates that an institution offers one or more doctoral-level academic degree programs.
- F. None of above.
Provenance (6 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a250e401288190ba12322c9c5f07c9 |
completed | Feb. 28, 2026, 2:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a302803f50819081a480c33f08b68a |
completed | Feb. 28, 2026, 2:58 p.m. |
| NEDg | Description generation | batch_69a30336ab2881908899f75c76b0d010 |
completed | Feb. 28, 2026, 3:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a303c507e08190b60abbb1740721b8 |
completed | Feb. 28, 2026, 3:03 p.m. |
| PD | Predicate disambiguation | batch_69a24eb59e808190811c20518f39b1cc |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.