Triple
T6122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Rylands University Library |
E121
|
entity |
| Predicate | hasSubjectFocus |
P450
|
FINISHED |
| Object | humanities |
—
|
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: humanities | Statement: [John Rylands University Library, hasSubjectFocus, humanities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectFocus Context triple: [John Rylands University Library, hasSubjectFocus, humanities]
-
A.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
C.
hasPrimaryFunction
Indicates that one entity serves as the main or principal function or role of another entity.
-
D.
focusPeriod
Indicates the specific time span during which attention, activity, or analysis is concentrated on something.
-
E.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2421836f08190b54fc40edeb1a96b |
completed | Feb. 28, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69a23fe064c881909496fd0e6b0e18d7 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.