Triple
T210526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HRK |
E4706
|
entity |
| Predicate | representsLevel |
P103
|
FINISHED |
| Object | tertiary education |
—
|
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: tertiary education | Statement: [HRK, representsLevel, tertiary education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsLevel Context triple: [HRK, representsLevel, tertiary education]
-
A.
meetsAtLevel
Indicates that two or more entities encounter or interact with each other at a specific hierarchical, structural, or progression level.
-
B.
hasLevel
Indicates that an entity possesses or is associated with a particular degree, rank, or stage within an ordered scale or hierarchy.
-
C.
hasRepresentationIn
chosen
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
D.
hasLevelDescription
Indicates that an entity is associated with a textual description specifying its level, degree, or stage.
-
E.
canRepresent
Indicates that one entity is capable of serving as a valid stand-in, proxy, or expression for another entity in a given context.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.