Triple
T2409357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbus State Community College |
E50349
|
entity |
| Predicate | hasDegreeLength |
P39271
|
FINISHED |
| Object | two years |
—
|
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: two years | Statement: [Columbus State Community College, hasDegreeLength, two years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDegreeLength Context triple: [Columbus State Community College, hasDegreeLength, two years]
-
A.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
B.
isDegreeOf
Indicates that one entity is an academic or professional degree held, pursued, or associated with another entity.
-
C.
hasFieldExtensionDegree
Indicates that one field is an extension of another and specifies the degree (dimension as a vector space) of this extension.
-
D.
hasDegreeOfFreedom
Indicates that one entity possesses a specific independent parameter or mode in which it can vary or move relative to another entity or within a system.
-
E.
typicalDegree
Indicates the usual or characteristic level, intensity, or extent to which something holds or applies in a given context.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abceaa42b88190a790355100fede3d |
completed | March 7, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:58 p.m.