Triple
T319961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winchester College |
E7791
|
entity |
| Predicate | offersBoarding |
P9404
|
FINISHED |
| Object | full boarding |
—
|
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: full boarding | Statement: [Winchester College, offersBoarding, full boarding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersBoarding Context triple: [Winchester College, offersBoarding, full boarding]
-
A.
offersViewOf
Indicates that one entity provides a vantage point from which another entity can be seen or visually appreciated.
-
B.
offersFeature
chosen
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
C.
offersActivity
Indicates that one entity provides or makes available a specific activity for another entity to participate in or use.
-
D.
offersServiceTo
Indicates that one entity provides or makes a service available for the benefit or use of another entity.
-
E.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea7edbc48190b9031bd1af48f72a |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.