Triple
T37354072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drew Scott |
E927404
|
entity |
| Predicate | startedRealEstateCareerIn |
P2214
|
FINISHED |
| Object | early 2000s |
—
|
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 2000s | Statement: [Drew Scott, startedRealEstateCareerIn, early 2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startedRealEstateCareerIn Context triple: [Drew Scott, startedRealEstateCareerIn, early 2000s]
-
A.
startedCareerWith
Indicates that an entity began its professional career associated with, employed by, or active for another specified entity.
-
B.
startedSoloCareer
Indicates that an individual began pursuing a professional career independently, separate from any previous group or collaborative affiliation.
-
C.
launchedCareerOf
Indicates that one entity’s actions, support, or involvement initiated or significantly advanced another entity’s professional career.
-
D.
startedStandUpCareerIn
Indicates that an individual began their stand-up comedy career in a particular place or context.
-
E.
careerStart
chosen
Indicates the point in time when an entity begins its professional career or main occupational activity.
- 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_69f76eb5e034819088e53ab5b7909a68 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a00ca5e907481909d391afd55938a1b |
completed | May 10, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_6a00ca2214348190a674a85ede709e2e |
completed | May 10, 2026, 6:10 p.m. |
Created at: May 3, 2026, 4:16 p.m.