Triple
T4311336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawson State Community College Bessemer Campus |
E94080
|
entity |
| Predicate | offersEnrollmentType |
P56389
|
FINISHED |
| Object | full-time study |
—
|
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: full-time study | Statement: [Lawson State Community College Bessemer Campus, offersEnrollmentType, full-time study]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersEnrollmentType Context triple: [Lawson State Community College Bessemer Campus, offersEnrollmentType, full-time study]
-
A.
offersPlanType
Indicates that one entity provides or makes available a specific type of plan to another entity or in a given context.
-
B.
offersCourseType
Indicates that an entity provides or makes available a course of a specified type.
-
C.
offeringType
Indicates the category or nature of what is being offered in a transaction or interaction (e.g., product, service, or other type of offering).
-
D.
offersServiceType
Indicates that one entity provides or makes available a specific type or category of service to another entity or the public.
-
E.
offersPanelType
Indicates that an entity provides or makes available a specific type of panel as part of its offerings.
- F. None of above. chosen
Provenance (4 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_69b3451886588190a3dd1305ea7c58dc |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b350d6cba08190a9440cee7b9dc40d |
completed | March 12, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69b34f4a07b08190a06ada0d9cbb14fb |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b35034cd248190bae09e9d090e13ec |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:11 p.m.