Triple
T1076560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calhoun College |
E23851
|
entity |
| Predicate | hasNotableTheme |
P7671
|
FINISHED |
| Object | reassessment of historical legacies |
—
|
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: reassessment of historical legacies | Statement: [Calhoun College, hasNotableTheme, reassessment of historical legacies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableTheme Context triple: [Calhoun College, hasNotableTheme, reassessment of historical legacies]
-
A.
notableTheme
chosen
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
-
B.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
C.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
D.
hasCentralTheme
Indicates that one entity serves as the primary or dominant theme or subject matter of another entity.
-
E.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b940d4848190930e73597afd1fcf |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.