Triple
T8406602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knight Library |
E198514
|
entity |
| Predicate | hasSubjectAreaFocus |
P43754
|
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: [Knight Library, hasSubjectAreaFocus, humanities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectAreaFocus Context triple: [Knight Library, hasSubjectAreaFocus, humanities]
-
A.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
B.
regionOfAcademicFocus
chosen
Indicates the academic subject area or discipline that an entity (such as a person or program) primarily concentrates on or specializes in.
-
C.
hasInstitutionalFocus
Indicates that an entity is oriented toward, concerned with, or primarily engaged in matters related to a particular institution or type of institution.
-
D.
hasAreaOfInterest
Indicates that an entity possesses or is associated with a particular area of interest or focus.
-
E.
hasSubjectOfStudy
Indicates that an entity (such as a person or organization) focuses on, researches, or specializes in a particular field or topic of study.
- 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_69ca8310df9c8190b25f16161cca3e41 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb831409308190981089c303ebaef4 |
completed | March 31, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:05 p.m.