Triple
T9356363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American studies |
E225149
|
entity |
| Predicate | academicSetting |
P19810
|
FINISHED |
| Object | universities |
—
|
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: universities | Statement: [American studies, academicSetting, universities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicSetting Context triple: [American studies, academicSetting, universities]
-
A.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
B.
academicUse
Indicates that something is intended for, suitable for, or used within an academic or educational context.
-
C.
academicAccess
Indicates that one entity has permission or the ability to use, enter, or benefit from academic resources, environments, or services provided by another entity.
-
D.
academicContext
chosen
Indicates the educational or scholarly setting, framework, or circumstances within which an activity, relationship, or piece of information takes place.
-
E.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4fee9d4c8190a7d121c9487ccca2 |
completed | April 1, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.