Triple
T28555017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bagrut |
E722980
|
entity |
| Predicate | creditUnitSystem |
P98440
|
FINISHED |
| Object | study units |
—
|
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: study units | Statement: [Bagrut, creditUnitSystem, study units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: creditUnitSystem Context triple: [Bagrut, creditUnitSystem, study units]
-
A.
unitSystem
Indicates the system of measurement units (such as metric or imperial) that is used to quantify associated values or attributes.
-
B.
designationUnit
chosen
Indicates that one entity serves as the unit or standard of measure used to designate, label, or quantify another entity.
-
C.
degreeSystem
Indicates a relationship where an entity’s degree or qualification is defined, classified, or governed by a particular educational or grading system.
-
D.
coordinateUnit
Indicates that one unit serves as a coordinate or reference unit relative to another in a measurement, spatial, or organizational context.
-
E.
basedUnit
Indicates that one unit is defined in terms of, or derived from, another more fundamental unit.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f652a492108190b885b955ce147d3c |
completed | May 2, 2026, 7:38 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 3:45 a.m.