Triple
T5540627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azerbaijani manat |
E145277
|
entity |
| Predicate | unitInDecimalSystem |
P5213
|
FINISHED |
| Object | 1 manat = 100 qəpik |
—
|
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: 1 manat = 100 qəpik | Statement: [Azerbaijani manat, unitInDecimalSystem, 1 manat = 100 qəpik]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unitInDecimalSystem Context triple: [Azerbaijani manat, unitInDecimalSystem, 1 manat = 100 qəpik]
-
A.
meterSystem
Indicates that one entity uses, is measured in, or is associated with a particular system of meters or measurement units.
-
B.
hasNumberSystem
chosen
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
-
C.
numericDecomposition
Indicates that a number is broken down into a set of component numbers or factors whose combination (e.g., sum or product) reconstructs the original value.
-
D.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
-
E.
numeralValueOfX
Indicates that a given numeral corresponds to, or represents, the numeric value of, the entity X.
- 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fc66cc08190b9b2a62098ecbdb1 |
completed | March 22, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.