Triple
T30543649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Political Science and Public Administration |
E777349
|
entity |
| Predicate | commonCourseTopic |
P43765
|
FINISHED |
| Object | public policy |
—
|
LITERAL 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: public policy | Statement: [College of Political Science and Public Administration, commonCourseTopic, public policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonCourseTopic Context triple: [College of Political Science and Public Administration, commonCourseTopic, public policy]
-
A.
typicalCourseTopic
chosen
Indicates that a given topic is commonly or characteristically covered as part of a particular course.
-
B.
commonCourse
Indicates that two or more entities share at least one course in common.
-
C.
coveredTopics
Indicates that certain subjects or themes have been addressed or included within a discussion, document, or activity.
-
D.
topicOfDialogue
Indicates that a particular subject or theme is the main focus of a dialogue or conversation between entities.
-
E.
typicalCourse
Indicates that one entity is a standard or commonly taken course associated with another entity, such as a program, curriculum, or field of study.
- F. None of above.
Provenance (3 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_69f2249d183c8190b79937c1768d2163 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: April 29, 2026, 8:19 p.m.