Triple
T8444093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Library Service |
E199626
|
entity |
| Predicate | offersResourceType |
P16209
|
FINISHED |
| Object | books |
—
|
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: books | Statement: [University Library Service, offersResourceType, books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersResourceType Context triple: [University Library Service, offersResourceType, books]
-
A.
offersServiceType
Indicates that one entity provides or makes available a specific type or category of service to another entity or the public.
-
B.
offersContentType
chosen
Indicates that one entity provides or makes available content of a specified type to another entity or context.
-
C.
offersEnrollmentType
Indicates that an entity provides or makes available a specific type or category of enrollment option.
-
D.
offersPlanType
Indicates that one entity provides or makes available a specific type of plan to another entity or in a given context.
-
E.
offersServiceIn
Indicates that a provider makes a particular service available within a specified location or jurisdiction.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe3122cfc8190ac6103fa4e4a7c45 |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.