Triple
T40235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrow School |
E795
|
entity |
| Predicate | tuitionFeeType |
P2737
|
FINISHED |
| Object | fee-paying |
—
|
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: fee-paying | Statement: [Harrow School, tuitionFeeType, fee-paying]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tuitionFeeType Context triple: [Harrow School, tuitionFeeType, fee-paying]
-
A.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
B.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
typeOfInstitution
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
E.
scholarshipEquivalency
Indicates that one scholarship is considered equal in value, coverage, or benefit to another scholarship or financial award.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b80f4a8819090d2bffe29824b90 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ab74c548190a54872e15c8394c3 |
completed | Feb. 28, 2026, 1:53 a.m. |
| PDg | Predicate description generation | batch_69a24b7fd2c08190a0057fe7aec6a1ee |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.