Triple
T15092740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Siena |
E360460
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Economics and Statistics
The Department of Economics and Statistics is an academic unit at the University of Siena focused on teaching and research in economics, statistics, and related quantitative social sciences.
|
E1137665
|
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: Department of Economics and Statistics | Statement: [University of Siena, hasDepartment, Department of Economics and Statistics]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Department of Economics and Statistics Context triple: [University of Siena, hasDepartment, Department of Economics and Statistics]
-
A.
Department of Economics, Business, Mathematics and Statistics
The Department of Economics, Business, Mathematics and Statistics is an academic unit of the University of Trieste that integrates teaching and research in economics, management, quantitative methods, and statistical sciences.
-
B.
Department of Econometrics and Business Statistics
The Department of Econometrics and Business Statistics is an academic unit specializing in quantitative analysis, statistical modeling, and data-driven decision-making in economics and business.
-
C.
Department of Economics
The Department of Economics is an academic unit of Gauhati University dedicated to teaching and research in economics and related fields.
-
D.
Department of Economics
The Department of Economics is an academic unit within the Haslam College of Business that focuses on teaching and research in economic theory, policy, and applied economics.
-
E.
Department of Economics
The Department of Economics is an academic unit within the Eller College of Management that focuses on teaching and research in economic theory, policy, and applied economics.
- 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: Department of Economics and Statistics Triple: [University of Siena, hasDepartment, Department of Economics and Statistics]
Generated description
The Department of Economics and Statistics is an academic unit at the University of Siena focused on teaching and research in economics, statistics, and related quantitative social sciences.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Department of Economics and Statistics Target entity description: The Department of Economics and Statistics is an academic unit at the University of Siena focused on teaching and research in economics, statistics, and related quantitative social sciences.
-
A.
Department of Economics, Business, Mathematics and Statistics
The Department of Economics, Business, Mathematics and Statistics is an academic unit of the University of Trieste that integrates teaching and research in economics, management, quantitative methods, and statistical sciences.
-
B.
Department of Econometrics and Business Statistics
The Department of Econometrics and Business Statistics is an academic unit specializing in quantitative analysis, statistical modeling, and data-driven decision-making in economics and business.
-
C.
Department of Economics
The Department of Economics is an academic unit of Gauhati University dedicated to teaching and research in economics and related fields.
-
D.
Department of Economics
The Department of Economics is an academic unit within the Haslam College of Business that focuses on teaching and research in economic theory, policy, and applied economics.
-
E.
Department of Economics
The Department of Economics at St. Stephen's College, University of Delhi, is a leading Indian academic department known for its rigorous economics curriculum and distinguished alumni in academia, policy, and industry.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0027925788190b955fdc6626adf7d |
completed | April 15, 2026, 9:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae1f406081909d4925474370da86 |
completed | May 9, 2026, 3:46 a.m. |
| NEDg | Description generation | batch_69feb2e869808190b691d95531dc7447 |
completed | May 9, 2026, 4:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feb3a61e008190aff906cae172a744 |
completed | May 9, 2026, 4:10 a.m. |
Created at: April 10, 2026, 3:04 a.m.