Triple
T12808269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asia/Ust-Nera |
E306200
|
entity |
| Predicate | principalLocalityType |
P16688
|
FINISHED |
| Object | urban-type settlement |
—
|
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: urban-type settlement | Statement: [Asia/Ust-Nera, principalLocalityType, urban-type settlement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: principalLocalityType Context triple: [Asia/Ust-Nera, principalLocalityType, urban-type settlement]
-
A.
placeType
chosen
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
B.
addressLocality
Indicates the city, town, or locality in which an address is situated.
-
C.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
D.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
E.
typeLocality
Indicates the specific geographic location where a specimen or taxon was originally found and formally described.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e808130819080f404b3a7462c2e |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:31 p.m.