Triple
T16230521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loomis Union School District |
E393966
|
entity |
| Predicate | employsStaffType |
P36133
|
FINISHED |
| Object | teachers |
—
|
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: teachers | Statement: [Loomis Union School District, employsStaffType, teachers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employsStaffType Context triple: [Loomis Union School District, employsStaffType, teachers]
-
A.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
B.
hasEmployees
chosen
Indicates that one entity employs one or more other entities as its workers or staff.
-
C.
hasWorkforceType
Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
-
D.
representedEmployeeType
Indicates that one entity serves as a representative or exemplar of a particular type or category of employee for another entity.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d29438c81909aa2724cc47bb959 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.