Triple
T9828465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Modern Languages and Literatures |
E238719
|
entity |
| Predicate | typicalDegreePrograms |
P63688
|
FINISHED |
| Object | bachelor’s degrees in modern languages |
—
|
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: bachelor’s degrees in modern languages | Statement: [Department of Modern Languages and Literatures, typicalDegreePrograms, bachelor’s degrees in modern languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDegreePrograms Context triple: [Department of Modern Languages and Literatures, typicalDegreePrograms, bachelor’s degrees in modern languages]
-
A.
typicalDegreeName
Indicates the standard or commonly used academic degree title associated with an educational program or qualification.
-
B.
typicalDegreeLevels
chosen
Indicates the usual or commonly expected academic degree levels associated with a given entity or context.
-
C.
academicProgramsMedium
Indicates the medium or format through which academic programs are delivered (e.g., online, in-person, hybrid).
-
D.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
-
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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3268fcc8190b7a028f224512e5f |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.