Triple
T738604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lithgow Public Library |
E14991
|
entity |
| Predicate | hasComputerWorkstations |
P19443
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lithgow Public Library, hasComputerWorkstations, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComputerWorkstations Context triple: [Lithgow Public Library, hasComputerWorkstations, yes]
-
A.
hasOnboardComputer
Indicates that one entity is equipped with or contains an onboard computer system.
-
B.
hasSupercomputer
Indicates that an entity possesses, controls, or is equipped with a supercomputer.
-
C.
hardwareUsedBy
Indicates that a piece of hardware is utilized or operated by a particular entity (such as a person, system, or organization).
-
D.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
E.
computes
Indicates that one entity performs a calculation or processing operation to produce a result from given data or inputs.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fc734c81908fbd36386d5746d6 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a64957ec81909fe2e2dbffd80ed3 |
completed | March 1, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:37 p.m.