Triple
T37945126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | לירה ישראלית |
E946583
|
entity |
| Predicate | סוג מטבעות |
P78439
|
FINISHED |
| Object | מטבעות מתכת |
—
|
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: מטבעות מתכת | Statement: [לירה ישראלית, סוג מטבעות, מטבעות מתכת]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: סוג מטבעות Context triple: [לירה ישראלית, סוג מטבעות, מטבעות מתכת]
-
A.
coinageType
chosen
Indicates the specific type or category of coinage associated with an entity, such as its denomination, series, or monetary classification.
-
B.
denominationType
Indicates the specific category or kind of denomination associated with an entity, such as its type within a broader classification of denominations.
-
C.
monetarySystemType
Indicates the type or classification of a monetary system associated with an entity.
-
D.
currencyDepicted
Indicates that one entity visually represents or shows the image or symbol of a particular currency on it.
-
E.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
- 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_69f76ef531ac8190ae6d99e5786e76ec |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc995dc2481908b3bd4217f8101e7 |
completed | May 6, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.