Triple
T15007142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Reference Library Reading Room |
E377737
|
entity |
| Predicate | usagePolicy |
P116336
|
FINISHED |
| Object | materials not for general loan |
—
|
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: materials not for general loan | Statement: [State Reference Library Reading Room, usagePolicy, materials not for general loan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usagePolicy Context triple: [State Reference Library Reading Room, usagePolicy, materials not for general loan]
-
A.
trailUsePolicy
Indicates the rules or guidelines governing how a trail may be accessed and used.
-
B.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
C.
dataPolicy
Indicates that one entity defines or governs how data related to another entity is collected, used, stored, or shared.
-
D.
usesPolicyRate
Indicates that one entity applies or bases its actions or decisions on a specified policy interest rate.
-
E.
endedPolicy
Indicates that a previously active policy has been brought to an end or terminated.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:55 a.m.