Triple
T38203816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kent College of Law |
E1009140
|
entity |
| Predicate | hasAlumniOfType |
P4387
|
FINISHED |
| Object | lawyers |
—
|
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: lawyers | Statement: [Kent College of Law, hasAlumniOfType, lawyers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlumniOfType Context triple: [Kent College of Law, hasAlumniOfType, lawyers]
-
A.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
B.
alumniType
Indicates the specific category or classification of an alumnus/alumna in relation to an institution (e.g., graduate, former student, honorary).
-
C.
hasAlumniField
Indicates a relationship where an entity is associated with a specific field or area of study in which its alumni specialized or graduated.
-
D.
hasNotableAlumniType
chosen
Indicates that an entity has notable alumni belonging to a specified category or type.
-
E.
hasAlumniOutcome
Indicates that an entity has a specific outcome or post-completion status associated with its alumni.
- 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_69f76dc94fcc8190bd2f55e81f9d6527 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe9b0276d48190b554fa22b043e6d8 |
completed | May 9, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69fe999692b081909921e1148d66f0ef |
completed | May 9, 2026, 2:19 a.m. |
Created at: May 3, 2026, 4:30 p.m.