Triple
T26681416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Training Ship Kennedy |
E672621
|
entity |
| Predicate | cadetCapacity |
P117034
|
FINISHED |
| Object | approximately 600 cadets |
—
|
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: approximately 600 cadets | Statement: [Training Ship Kennedy, cadetCapacity, approximately 600 cadets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cadetCapacity Context triple: [Training Ship Kennedy, cadetCapacity, approximately 600 cadets]
-
A.
admittedCadetsAged
Indicates that an institution has admitted cadets who are of a specified age or within a specified age range.
-
B.
hasCorpsOfCadets
Indicates that an institution maintains an organized corps of cadets as part of its structure or programs.
-
C.
hasSchoolCapacity
chosen
Indicates that an educational institution can accommodate a specified maximum number of students or occupants.
-
D.
soldiersCapacity
Indicates the maximum number of soldiers that an entity can hold, support, or accommodate.
-
E.
typeOfCadetForce
Indicates the specific category or kind of cadet force to which an entity belongs.
- 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_69eecda13424819092b17942c4edf722 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6173a2a208190a8e8bc9513984115 |
completed | May 2, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:20 a.m.