Triple
T1169172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Truth and Service |
E24873
|
entity |
| Predicate | mottoOfType |
P504
|
FINISHED |
| Object | public historically Black university |
—
|
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: public historically Black university | Statement: [Truth and Service, mottoOfType, public historically Black university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mottoOfType Context triple: [Truth and Service, mottoOfType, public historically Black university]
-
A.
mottoType
chosen
Indicates the specific category or kind of motto that characterizes the relationship between an entity and its motto.
-
B.
mottoOriginalLanguage
Indicates the language in which a motto was originally formulated or expressed.
-
C.
motto
Indicates that one entity serves as the guiding phrase, slogan, or maxim associated with another entity.
-
D.
isMottoOf
Indicates that a phrase or expression serves as the official motto associated with a particular entity.
-
E.
mottoStyle
Indicates the stylistic form or presentation in which a motto is expressed.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce821b481908bc278a3fa7973f4 |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.