Triple
T9786304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TurkishLanguageSchools |
E237496
|
entity |
| Predicate | mayEmploy |
P58475
|
FINISHED |
| Object | native Turkish-speaking 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: native Turkish-speaking teachers | Statement: [TurkishLanguageSchools, mayEmploy, native Turkish-speaking teachers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayEmploy Context triple: [TurkishLanguageSchools, mayEmploy, native Turkish-speaking teachers]
-
A.
mayWorkIn
Indicates that an entity is allowed or has the possibility to work in a particular place, organization, or context.
-
B.
employedTo
Indicates that one entity is hired or engaged to perform work, services, or duties for another entity.
-
C.
employedApproximately
Indicates that one entity employs another in a manner where the number, duration, or extent of employment is approximate rather than exact.
-
D.
canHire
chosen
Indicates that one entity has the authority or ability to employ or recruit another entity.
-
E.
employedPeople
Indicates that there exists a relationship where people are currently working in jobs or positions, typically under an employer.
- 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_69ca84da927881909bda80caecad6010 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda2107f688190b2cab1509c508319 |
completed | April 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69cd03d77c6c81909b675955bf113320 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:27 p.m.