Triple
T1600547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cisco Certified Internetwork Expert |
E34380
|
entity |
| Predicate | hasExamComponent |
P24108
|
FINISHED |
| Object | written exam |
—
|
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: written exam | Statement: [Cisco Certified Internetwork Expert, hasExamComponent, written exam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExamComponent Context triple: [Cisco Certified Internetwork Expert, hasExamComponent, written exam]
-
A.
hasCurriculumComponent
chosen
Indicates that one curriculum or educational program includes or is composed of a particular component, module, or element.
-
B.
hasCompetence
Indicates that an entity possesses the ability, skill, or qualification to perform a specific task or function effectively.
-
C.
hasQualification
Indicates that an entity possesses a specific qualification, credential, or competency.
-
D.
passedExam
Indicates that an entity has successfully met the required criteria to pass a particular exam.
-
E.
hasQualificationStructure
Indicates that an entity is associated with a specific configuration or pattern of qualifications (e.g., degrees, certifications, or credentials) that define how those qualifications are organized or structured.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a95b02cd448190be8e3db9a5a7bac0 |
completed | March 5, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69a907c1cad08190b9728dd557f39aa0 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.