Triple
T315526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Wayne Assembly |
E7696
|
entity |
| Predicate | hasWorkforceType |
P11922
|
FINISHED |
| Object | hourly employees |
—
|
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: hourly employees | Statement: [Fort Wayne Assembly, hasWorkforceType, hourly employees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkforceType Context triple: [Fort Wayne Assembly, hasWorkforceType, hourly employees]
-
A.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
B.
hasTypeOfOrganization
Indicates that an entity is classified as belonging to a particular type or category of organization.
-
C.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
-
D.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
-
E.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea6462148190825acc57f6d2adaf |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea08878c8190a5e8a90f620a3888 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.