Triple
T2144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School of Humanities, Arts, and Social Sciences |
E39
|
entity |
| Predicate | hasTypeOfDegree |
P49
|
FINISHED |
| Object | undergraduate degree |
—
|
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: undergraduate degree | Statement: [School of Humanities, Arts, and Social Sciences, hasTypeOfDegree, undergraduate degree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfDegree Context triple: [School of Humanities, Arts, and Social Sciences, hasTypeOfDegree, undergraduate degree]
-
A.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
offersDegree
chosen
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
C.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
D.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
E.
hasSchool
Indicates that an entity possesses, is associated with, or is served by a particular school.
- 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_69a22cde80848190b62c5f556b4d62ba |
completed | Feb. 27, 2026, 11:46 p.m. |
| NER | Named-entity recognition | batch_69a2316d88a08190b2e03041674b5674 |
completed | Feb. 28, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69a230c3ee4481908216244c38aa8aef |
completed | Feb. 28, 2026, 12:03 a.m. |
Created at: Feb. 27, 2026, 11:48 p.m.