Triple
T16610785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bauhaus-Universität Weimar |
E403558
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
BUW
BUW is the abbreviation for Bauhaus-Universität Weimar, a German university known for its programs in architecture, design, art, and media.
|
E1222952
|
NE FINISHED |
How this triple was built (4 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: BUW | Statement: [Bauhaus-Universität Weimar, abbreviation, BUW]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BUW Context triple: [Bauhaus-Universität Weimar, abbreviation, BUW]
-
A.
BU
BU is the commonly used abbreviation for Bloomsburg University of Pennsylvania, a public university located in Bloomsburg, Pennsylvania.
-
B.
BU
BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
-
C.
BU
BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
-
D.
BU
BU is a private university in Peoria, Illinois, known for its comprehensive academic programs and strong emphasis on experiential learning.
-
E.
BU
BU is a modern public university located in Bournemouth, England, known for its strong industry links and career-focused courses, particularly in media, business, and tourism.
- 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: BUW Triple: [Bauhaus-Universität Weimar, abbreviation, BUW]
Generated description
BUW is the abbreviation for Bauhaus-Universität Weimar, a German university known for its programs in architecture, design, art, and media.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BUW Target entity description: BUW is the abbreviation for Bauhaus-Universität Weimar, a German university known for its programs in architecture, design, art, and media.
-
A.
BU
BU is a historic vehicle registration prefix that was once used to identify motor vehicles registered in Buckinghamshire, England.
-
B.
BU
BU is a modern public university located in Bournemouth, England, known for its strong industry links and career-focused courses, particularly in media, business, and tourism.
-
C.
BU
BU is the commonly used abbreviation for Bloomsburg University of Pennsylvania, a public university located in Bloomsburg, Pennsylvania.
-
D.
BU
BU is a major private research university in Boston, Massachusetts, known for its diverse academic programs and global student body.
-
E.
BU
BU is a private university in Peoria, Illinois, known for its comprehensive academic programs and strong emphasis on experiential learning.
- F. None of above. chosen
Provenance (5 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3609572508190a5d7e6c3e0a8cf95 |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0075aca5c0819092637e0d83ce8ac0 |
completed | May 10, 2026, 12:10 p.m. |
| NEDg | Description generation | batch_6a00783fcde08190963ce80fcf4aac90 |
completed | May 10, 2026, 12:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0078a78ee08190887e93c08edbaead |
completed | May 10, 2026, 12:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.