Triple
T38100212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Staten |
E951354
|
entity |
| Predicate | joinedEmployer |
P49123
|
FINISHED |
| Object | Microsoft Studios |
—
|
NE NERFINISHED |
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: Microsoft Studios | Statement: [Joseph Staten, joinedEmployer, Microsoft Studios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: joinedEmployer Context triple: [Joseph Staten, joinedEmployer, Microsoft Studios]
-
A.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
B.
employedTo
Indicates that one entity is hired or engaged to perform work, services, or duties for another entity.
-
C.
employerOrPartner
Indicates that one entity is either the employer of, or a business partner with, another entity.
-
D.
employerService
Indicates that one entity provides employment-related services or functions to another entity, typically in the role of an employer.
-
E.
employerRelationship
chosen
Indicates a relationship in which one entity acts as the employer of another, having authority to hire, direct, and compensate the other party for work performed.
- 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_69f76f04960c8190a83f14ae4c67f5bc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4748843c8190931432653be4890c |
completed | May 7, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69fc45646ce481908caf292ff9f06e15 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.