Triple
T6375626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of King’s College |
E143457
|
entity |
| Predicate | offersResidence |
P40724
|
FINISHED |
| Object | on-campus housing |
—
|
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: on-campus housing | Statement: [University of King’s College, offersResidence, on-campus housing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersResidence Context triple: [University of King’s College, offersResidence, on-campus housing]
-
A.
boardingOffered
chosen
Indicates that the provision of boarding or lodging services is being made available to one or more entities.
-
B.
offersAccess
Indicates that one entity provides another entity with the ability or permission to use, enter, or interact with a resource, service, or location.
-
C.
offering
Indicates that one entity presents or provides something to another entity, typically as a gift, contribution, or proposal.
-
D.
offersViewOf
Indicates that one entity provides a vantage point from which another entity can be seen or visually appreciated.
-
E.
offersOutcome
Indicates that one entity provides or makes available a particular result, consequence, or benefit to another entity.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0683bfc7081908b15c3c9a3c72e7b |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ee055081908c79a1d151bd74cd |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.