Triple
T24205487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Advanced Individual Training |
E600092
|
entity |
| Predicate | typeOfSkill |
P132821
|
FINISHED |
| Object | occupational specialty skills |
—
|
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: occupational specialty skills | Statement: [Advanced Individual Training, typeOfSkill, occupational specialty skills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSkill Context triple: [Advanced Individual Training, typeOfSkill, occupational specialty skills]
-
A.
skillType
chosen
Indicates the specific category or kind of skill that characterizes or classifies an associated skill-related entity or action.
-
B.
skillSet
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
-
C.
skilledIn
Indicates that an entity possesses ability, expertise, or proficiency in performing or using another entity (such as a task, tool, or domain).
-
D.
describesSkill
Indicates that one entity provides a description or characterization of another entity’s skill or ability.
-
E.
skillAssessed
Indicates that an entity’s skill or competency has been evaluated or measured, typically by another agent or process.
- 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27ca52cb881908c99913ea93bc88e |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:37 p.m.