Triple
T10760886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UA |
E253821
|
entity |
| Predicate | hasMottoInFrench |
P4406
|
FINISHED |
| Object | L’université à taille humaine |
—
|
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: L’université à taille humaine | Statement: [UA, hasMottoInFrench, L’université à taille humaine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMottoInFrench Context triple: [UA, hasMottoInFrench, L’université à taille humaine]
-
A.
languageOfMotto
chosen
Indicates the language in which a motto is written or expressed.
-
B.
mottoOriginalLanguage
Indicates the language in which a motto was originally formulated or expressed.
-
C.
hasMottoLikeFunction
Indicates that something serves a role or function similar to a motto, typically expressing a guiding principle, slogan, or core message.
-
D.
usesMotto
Indicates that one entity adopts or employs a particular motto as its guiding phrase or slogan.
-
E.
hasMottoLanguageContext
Indicates that a motto is associated with a specific language context in which it is expressed or interpreted.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d731a14c7481909c6f4f9b15dc130f |
completed | April 9, 2026, 4:57 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.