Triple
T478237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urbana Free Library |
E9107
|
entity |
| Predicate | hasCatalog |
P9162
|
FINISHED |
| Object | online public access catalog |
—
|
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: online public access catalog | Statement: [Urbana Free Library, hasCatalog, online public access catalog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCatalog Context triple: [Urbana Free Library, hasCatalog, online public access catalog]
-
A.
hasOnlineCatalog
chosen
Indicates that an entity provides a catalog of its items or offerings that is accessible via the internet.
-
B.
hasProduct
Indicates that an entity possesses, offers, or is associated with a particular product.
-
C.
hasMajorCategory
Indicates that something is associated with or classified under a primary, overarching category.
-
D.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
E.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03f3fbc81909af6e4496d5e6c2a |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf017548190ae38ff3314a1ffa3 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.