Triple
T6657233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neighborhood Youth Corps |
E151376
|
entity |
| Predicate | typicalWorksites |
P1527
|
FINISHED |
| Object | schools |
—
|
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: schools | Statement: [Neighborhood Youth Corps, typicalWorksites, schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWorksites Context triple: [Neighborhood Youth Corps, typicalWorksites, schools]
-
A.
typicalEmployer
Indicates that one entity is the kind of organization or person that commonly or usually employs the other entity.
-
B.
locationOfWork
chosen
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
C.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
D.
ownsWork
Indicates that one entity has legal ownership or proprietary rights over a particular work or creation.
-
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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9d53848190ac75523c157249c6 |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad071b0081909b96dd4b93414bd1 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.