Triple
T19713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cairo University |
E391
|
entity |
| Predicate | hasMottoLanguage |
P207
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [Cairo University, hasMottoLanguage, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMottoLanguage Context triple: [Cairo University, hasMottoLanguage, Arabic]
-
A.
mottoType
Indicates the specific category or kind of motto that characterizes the relationship between an entity and its motto.
-
B.
motto
Indicates that one entity serves as the guiding phrase, slogan, or maxim associated with another entity.
-
C.
hasSignificantLanguage
chosen
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
-
D.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
E.
hasMascot
Indicates that an entity is represented or symbolized by a particular mascot.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.