Triple
T13084940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLUSTER |
E310306
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object |
Consortium Linking Universities of Science and Technology for Education and Research
The Consortium Linking Universities of Science and Technology for Education and Research (CLUSTER) is an international network of leading science and technology universities that collaborates on education, research, and academic exchange initiatives.
|
E1021096
|
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: Consortium Linking Universities of Science and Technology for Education and Research | Statement: [CLUSTER, fullName, Consortium Linking Universities of Science and Technology for Education and Research]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Consortium Linking Universities of Science and Technology for Education and Research Context triple: [CLUSTER, fullName, Consortium Linking Universities of Science and Technology for Education and Research]
-
A.
Global Alliance of Technological Universities
The Global Alliance of Technological Universities is an international consortium of leading research-intensive science and engineering universities that collaborate on education, innovation, and global technological challenges.
-
B.
Centre for Collaboration with Education Networks
The Centre for Collaboration with Education Networks is a unit within the Norwegian Institute of Public Health that works with schools and educational stakeholders to promote health, knowledge sharing, and evidence-based practices in the education sector.
-
C.
European Consortium of Innovative Universities
The European Consortium of Innovative Universities is a network of forward-looking European universities focused on innovation in education, research, and regional engagement.
-
D.
Centre for Collaboration with Training Networks
The Centre for Collaboration with Training Networks is a specialized unit within the Norwegian Institute of Public Health that supports and coordinates research training partnerships and collaborative networks.
-
E.
Centre for Collaboration with Universities
The Centre for Collaboration with Universities is a unit within the Norwegian Institute of Public Health that fosters research partnerships and academic cooperation with higher education institutions.
- 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: Consortium Linking Universities of Science and Technology for Education and Research Triple: [CLUSTER, fullName, Consortium Linking Universities of Science and Technology for Education and Research]
Generated description
The Consortium Linking Universities of Science and Technology for Education and Research (CLUSTER) is an international network of leading science and technology universities that collaborates on education, research, and academic exchange initiatives.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Consortium Linking Universities of Science and Technology for Education and Research Target entity description: The Consortium Linking Universities of Science and Technology for Education and Research (CLUSTER) is an international network of leading science and technology universities that collaborates on education, research, and academic exchange initiatives.
-
A.
Global Alliance of Technological Universities
The Global Alliance of Technological Universities is an international consortium of leading research-intensive science and engineering universities that collaborate on education, innovation, and global technological challenges.
-
B.
Centre for Collaboration with Education Networks
The Centre for Collaboration with Education Networks is a unit within the Norwegian Institute of Public Health that works with schools and educational stakeholders to promote health, knowledge sharing, and evidence-based practices in the education sector.
-
C.
European Consortium of Innovative Universities
The European Consortium of Innovative Universities is a network of forward-looking European universities focused on innovation in education, research, and regional engagement.
-
D.
Centre for Collaboration with Training Networks
The Centre for Collaboration with Training Networks is a specialized unit within the Norwegian Institute of Public Health that supports and coordinates research training partnerships and collaborative networks.
-
E.
Centre for Collaboration with Universities
The Centre for Collaboration with Universities is a unit within the Norwegian Institute of Public Health that fosters research partnerships and academic cooperation with higher education institutions.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981361e8c819099376435aa3a7aa3 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d61060188190911eb3e135dc25ac |
completed | May 3, 2026, 4:58 a.m. |
| NEDg | Description generation | batch_69f6dae595908190b27980e48514cda5 |
completed | May 3, 2026, 5:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6db8f68a4819091d8e67d9c8eec81 |
completed | May 3, 2026, 5:22 a.m. |
Created at: April 9, 2026, 9:02 p.m.