Triple
T20508099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worksop College |
E503485
|
entity |
| Predicate | hasBoardingPupils |
P16557
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Worksop College, hasBoardingPupils, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardingPupils Context triple: [Worksop College, hasBoardingPupils, yes]
-
A.
hasBoardingStudents
chosen
Indicates that an educational institution accommodates students who reside on campus as boarders.
-
B.
hasBoardingSchool
Indicates that an entity operates, contains, or is associated with a boarding school where students both study and reside.
-
C.
hadPupilsFrom
Indicates that an entity served as a teacher or mentor to the specified pupils.
-
D.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
E.
hasBoardingType
Indicates the specific manner or method by which an entity is boarded or accessed (e.g., how passengers or items are taken on).
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69dc8f3c881908ed2e0257a057e73 |
completed | April 20, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:36 a.m.