Triple
T14934007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ishkashimi |
E372341
|
entity |
| Predicate | notUsedInDomain |
P116723
|
FINISHED |
| Object | formal education |
—
|
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: formal education | Statement: [Ishkashimi, notUsedInDomain, formal education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notUsedInDomain Context triple: [Ishkashimi, notUsedInDomain, formal education]
-
A.
usedInDomain
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
-
B.
notUsedAt
Indicates that a particular entity is not utilized, applied, or active at a specified location, time, or context.
-
C.
notAutomaticallyUsedBy
Indicates that something is not used by another entity in an automatic or default manner and instead requires explicit action or configuration to be used.
-
D.
notUsedOnModel
Indicates that a particular item, component, or feature is not applied, installed, or utilized on the specified model.
-
E.
notUsedInCountry
Indicates that a given item, resource, or entity is not utilized, applied, or in operation within a specified country.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded646a0808190ba5c0c91bde011c5 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:37 a.m.