Triple
T2347659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Cod Community College |
E45167
|
entity |
| Predicate | hasCredentialType |
P6396
|
FINISHED |
| Object | academic certificates |
—
|
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: academic certificates | Statement: [Cape Cod Community College, hasCredentialType, academic certificates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCredentialType Context triple: [Cape Cod Community College, hasCredentialType, academic certificates]
-
A.
credentialType
chosen
Indicates the specific kind or category of credential associated with an entity or relationship.
-
B.
hasContactType
Indicates the specific kind or category of contact relationship that exists between two entities.
-
C.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
D.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
E.
hasCriterionType
Indicates that something is associated with or classified by a specific type of criterion used for evaluation or decision-making.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abcade3c808190ab3803538ccbe620 |
completed | March 7, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69abc59616a8819099711834e6f1ccd6 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:52 p.m.