Triple
T38013270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MRCS |
E948421
|
entity |
| Predicate | typicalTimingInCareer |
P144081
|
FINISHED |
| Object | early years of surgical training |
—
|
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: early years of surgical training | Statement: [MRCS, typicalTimingInCareer, early years of surgical training]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTimingInCareer Context triple: [MRCS, typicalTimingInCareer, early years of surgical training]
-
A.
timeInCareer
chosen
Indicates the point or duration within an entity’s professional or occupational trajectory at which a related event, status, or condition occurs.
-
B.
refersToEraOfCareer
Indicates that one entity specifies or denotes the particular era or phase within another entity’s career.
-
C.
startTimeOfProfessionalCareer
Indicates the point in time when an individual’s professional career formally begins.
-
D.
activeYearsInCareer
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
E.
appliesDuringCareerPhase
Indicates that something is relevant or in effect only during a specified phase of an entity’s career.
- 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_69f76efc10448190aff5fb566b98f952 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:20 p.m.