Triple
T199288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egyptian pound |
E4066
|
entity |
| Predicate | subunitNameInArabic |
P6450
|
FINISHED |
| Object | قرش |
—
|
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: قرش | Statement: [Egyptian pound, subunitNameInArabic, قرش]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subunitNameInArabic Context triple: [Egyptian pound, subunitNameInArabic, قرش]
-
A.
subunitType
Indicates that one entity is a specific kind or classification of subunit within the structure or composition of another entity.
-
B.
subunitNamePlural
Indicates that an entity has multiple subunits and specifies the pluralized name used to refer collectively to those subunits.
-
C.
hasNameInArabic
chosen
Indicates that an entity is associated with a specific name expressed in the Arabic language.
-
D.
formerSubunit
Indicates that one entity was previously a subunit or subordinate part of another entity, but no longer holds that status.
-
E.
subunitRatio
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcc6dc88190b8c24b485588dfe4 |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.