Triple
T15108024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wageningen University & Research |
E360839
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
WUR
WUR is a leading Dutch institution specializing in life sciences, agriculture, food, and environmental research and education.
|
E1138525
|
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: WUR | Statement: [Wageningen University & Research, shortName, WUR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WUR Context triple: [Wageningen University & Research, shortName, WUR]
-
A.
UWr
UWr is the commonly used abbreviation for the University of Wrocław, a major public research university located in Wrocław, Poland.
-
B.
WÜ
WÜ is the vehicle registration code for the city and district of Würzburg in the Lower Franconia region of Bavaria, Germany.
-
C.
UWA
UWA is a regional public university in Livingston, Alabama, known for its programs in education, liberal arts, and natural sciences.
-
D.
UWA
UWA is a leading Australian public research university based in Perth, known for its strong academic programs and sandstone campus.
-
E.
UWA
UWA is the acronym for the Uganda Wildlife Authority, the government agency responsible for managing and conserving Uganda’s wildlife and protected areas.
- 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: WUR Triple: [Wageningen University & Research, shortName, WUR]
Generated description
WUR is a leading Dutch institution specializing in life sciences, agriculture, food, and environmental research and education.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WUR Target entity description: WUR is a leading Dutch institution specializing in life sciences, agriculture, food, and environmental research and education.
-
A.
UWr
UWr is the commonly used abbreviation for the University of Wrocław, a major public research university located in Wrocław, Poland.
-
B.
WÜ
WÜ is the vehicle registration code for the city and district of Würzburg in the Lower Franconia region of Bavaria, Germany.
-
C.
UWA
UWA is a regional public university in Livingston, Alabama, known for its programs in education, liberal arts, and natural sciences.
-
D.
UWA
UWA is a leading Australian public research university based in Perth, known for its strong academic programs and sandstone campus.
-
E.
UWA
UWA is the acronym for the Uganda Wildlife Authority, the government agency responsible for managing and conserving Uganda’s wildlife and protected areas.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058af8988190977d998f85893836 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7e912ac8190bd0e0c9cdbbd0194 |
completed | May 9, 2026, 4:28 a.m. |
| NEDg | Description generation | batch_69feba1d256c8190ba13379d0cb8135c |
completed | May 9, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feba93c4cc819083c683210d1f03f8 |
completed | May 9, 2026, 4:39 a.m. |
Created at: April 10, 2026, 3:05 a.m.