Triple
T28807400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Arts and Letters, University of Notre Dame |
E727416
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object |
Department of Political Science, University of Notre Dame
The Department of Political Science at the University of Notre Dame is a leading academic unit known for its research and teaching in areas such as American politics, comparative politics, international relations, political theory, and constitutional studies.
|
E1833867
|
NE FINISHED |
How this triple was built (2 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 Political Science, University of Notre Dame | Statement: [College of Arts and Letters, University of Notre Dame, hasDepartment, Department of Political Science, University of Notre Dame]
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 Political Science, University of Notre Dame Triple: [College of Arts and Letters, University of Notre Dame, hasDepartment, Department of Political Science, University of Notre Dame]
Generated description
The Department of Political Science at the University of Notre Dame is a leading academic unit known for its research and teaching in areas such as American politics, comparative politics, international relations, political theory, and constitutional studies.
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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f658af9cd8819099951b89f7b7bcc2 |
completed | May 2, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a24a27e0b608190b0f731eec8854d93 |
completed | June 6, 2026, 10:43 p.m. |
| NEDg | Description generation | batch_6a24a667d6d08190917858826b13e134 |
completed | June 6, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a24aaa014a081908831ccb241673fae |
completed | June 6, 2026, 11:17 p.m. |
Created at: April 28, 2026, 6:29 a.m.