Triple
T16136011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dzyarzhynsk |
E391527
|
entity |
| Predicate | currentSubdivisionType |
P36805
|
FINISHED |
| Object | district-level town |
—
|
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: district-level town | Statement: [Dzyarzhynsk, currentSubdivisionType, district-level town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentSubdivisionType Context triple: [Dzyarzhynsk, currentSubdivisionType, district-level town]
-
A.
representsCurrentSubdivision
Indicates that one entity is the current administrative or organizational subdivision of another entity.
-
B.
primarySubdivisionOf
Indicates that one administrative or territorial unit is the main first-level subdivision within a larger political or geographic entity.
-
C.
hasTypeOfSubdivision
chosen
Indicates that one administrative or territorial unit is classified as a specific kind or category of subdivision.
-
D.
subdivisionType0
Indicates that the referenced entity is classified as the primary (level 0) type of administrative or territorial subdivision within a larger jurisdiction.
-
E.
countrySubdivisionType
Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a05148c8190bc2b98217fda23cc |
completed | April 17, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.