Triple
T32130162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Hope Bobeck |
E820618
|
entity |
| Predicate | professionLevel |
P100365
|
FINISHED |
| Object | young physician |
—
|
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: young physician | Statement: [Dr. Hope Bobeck, professionLevel, young physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionLevel Context triple: [Dr. Hope Bobeck, professionLevel, young physician]
-
A.
qualificationLevel
Indicates the degree or rank of competence, certification, or formal credentials required for or possessed in relation to something.
-
B.
professionalClass
chosen
Indicates that an entity belongs to, or is categorized within, a particular professional or occupational class.
-
C.
levelOfProfessionalism
Indicates the degree to which an entity conducts itself in a manner consistent with accepted professional standards and behavior.
-
D.
professionalScope
Indicates the range of activities, responsibilities, or roles that fall within a person’s or organization’s recognized professional duties or expertise.
-
E.
professionalTierInCountry
Indicates the professional level or tier that an entity holds within the context of a specific country.
- 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_69f349039e0c819091c7a7d322e3f46d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b96f3f108190a138524eb7e07fbf |
completed | May 3, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:29 a.m.