Triple
T23719604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Boone Regional Library |
E586103
|
entity |
| Predicate | hasBookmobileService |
P153687
|
FINISHED |
| Object | Bookmobile |
—
|
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: Bookmobile | Statement: [Daniel Boone Regional Library, hasBookmobileService, Bookmobile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBookmobileService Context triple: [Daniel Boone Regional Library, hasBookmobileService, Bookmobile]
-
A.
hasLibraryBranch
Indicates that an entity possesses or is associated with one or more library branches as part of its organizational structure or services.
-
B.
hasBorrowingSystem
Indicates that an entity possesses or employs a system or mechanism for borrowing items, resources, or services.
-
C.
isLendingLibrary
Indicates that an entity functions as a library that lends items (such as books or media) to users.
-
D.
hasCirculationFeature
Indicates that an entity possesses a specific feature related to movement or flow within a system, such as circulation paths, routes, or mechanisms.
-
E.
servedByLibrary
Indicates that an entity receives services, resources, or support from a particular library.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b77e2dc081908aef7a4c9b188dbd |
completed | April 29, 2026, 7:47 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f15b453da88190889a8d9b21727958 |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 17, 2026, 7 p.m.