Triple
T22754744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bakhmach Uyezd |
E562807
|
entity |
| Predicate | centralSettlementType |
P1068
|
FINISHED |
| Object | 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: town | Statement: [Bakhmach Uyezd, centralSettlementType, town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centralSettlementType Context triple: [Bakhmach Uyezd, centralSettlementType, town]
-
A.
mainSettlement
Indicates that one settlement serves as the primary or most important settlement associated with a given area, region, or administrative unit.
-
B.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
C.
centerType
Indicates the classification or category of a center (e.g., type of facility, institution, or hub) associated with an entity.
-
D.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
E.
settlementType
chosen
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179bc48788190b3deb9287d02cb2c |
completed | April 29, 2026, 3:23 a.m. |
| PD | Predicate disambiguation | batch_69eed2b88d88819096015deb6a648801 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:25 p.m.