Triple
T20850043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avancez |
E513330
|
entity |
| Predicate | institutionTypeUsingMotto |
P142090
|
FINISHED |
| Object | technical 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: technical university | Statement: [Avancez, institutionTypeUsingMotto, technical university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: institutionTypeUsingMotto Context triple: [Avancez, institutionTypeUsingMotto, technical university]
-
A.
hasMottoOfParentInstitution
Indicates that an institution has a motto that is inherited from or identical to the motto of its parent institution.
-
B.
organizationMottoContext
Indicates the contextual relationship between an organization and the motto or slogan associated with it.
-
C.
countryOfInstitutionUsingMotto
Indicates the country in which an institution that uses a given motto is located or associated.
-
D.
isMottoOf
Indicates that a phrase or expression serves as the official motto associated with a particular entity.
-
E.
mottoOfOrganizationLocation
Indicates that a particular motto is associated with an organization specifically in a given location.
- F. None of above. chosen
Provenance (4 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c352ca8c819094545dbe67bfe3dc |
completed | April 21, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a593f481908beb457c29f1ce73 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:43 p.m.