Triple
T23665966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Part 404 Subpart P – Medical-Vocational Guidelines |
E584576
|
entity |
| Predicate | workExperienceCategory |
P22109
|
FINISHED |
| Object | unskilled work |
—
|
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: unskilled work | Statement: [Part 404 Subpart P – Medical-Vocational Guidelines, workExperienceCategory, unskilled work]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workExperienceCategory Context triple: [Part 404 Subpart P – Medical-Vocational Guidelines, workExperienceCategory, unskilled work]
-
A.
employmentBasedCategory
Indicates that one entity’s classification or status is determined by its relationship to employment, such as being based on a specific job, role, or work-related category.
-
B.
workExplores
Indicates that a work investigates, examines, or delves into a particular subject, theme, or concept.
-
C.
experienceType
chosen
Indicates the specific kind or category of experience associated with an entity or event.
-
D.
typeOfExperience
Indicates that one entity specifies the category or nature of an experience associated with another entity.
-
E.
employmentCharacteristic
Indicates a specific attribute, condition, or quality associated with a person’s employment or job situation.
- 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_69e24901421881908c17a5293bdd4a8e |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b40b8bd48190922c7252e71a5421 |
completed | April 29, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69f118dd13008190a8799b4e9cadbd79 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:50 p.m.