Triple
T18867931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MHL |
E461488
|
entity |
| Predicate | professionalPathway |
P113631
|
FINISHED |
| Object | step below KHL |
—
|
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: step below KHL | Statement: [MHL, professionalPathway, step below KHL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalPathway Context triple: [MHL, professionalPathway, step below KHL]
-
A.
professionalPathwayFor
chosen
Indicates that one entity serves as a professional development route, track, or sequence leading toward a particular career or occupational role for another entity.
-
B.
careerPath
Indicates the progression or sequence of roles, positions, or occupations that an individual follows over time in their professional life.
-
C.
regulatedProfessionPathway
Indicates that an entity follows an officially controlled or legally mandated pathway to enter or practice a regulated profession.
-
D.
professionalOutcome
Indicates the resulting professional status, achievement, or consequence that arises from a person’s work-related actions, experiences, or decisions.
-
E.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
- 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_69d8dcfb7b9c8190854e7b171b98ea2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c2a6d1d081909b6dab2a5166a317 |
completed | April 20, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69e48d2166b88190add38de96cedc65c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:57 a.m.