Triple
T4924370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John McGraw |
E110540
|
entity |
| Predicate | managerialCareerStart |
P59499
|
FINISHED |
| Object | 1899 |
—
|
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: 1899 | Statement: [John McGraw, managerialCareerStart, 1899]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: managerialCareerStart Context triple: [John McGraw, managerialCareerStart, 1899]
-
A.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
B.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
-
C.
studCareerStart
Indicates the point in time when a student's professional or academic career begins.
-
D.
studCareerBegan
Indicates that a student's professional or academic career started at a specified time or institution.
-
E.
partOfCareer
Indicates that one entity represents a role, position, or period that forms a component or phase within another entity’s overall career.
- F. None of above. chosen
Provenance (4 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_69bd4413f9908190afcff44d7929cc4c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffeb86c8190a2fabe1ae1d54118 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3695c8819094e7ad2f6d4ba1ac |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd6d3806f881909c06687e9e57b67f |
completed | March 20, 2026, 3:52 p.m. |
Created at: March 20, 2026, 1:30 p.m.