Triple
T31055857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maskoŭskaja line |
E791394
|
entity |
| Predicate | servesLandmarks |
P43158
|
FINISHED |
| Object | key districts and landmarks of Minsk |
—
|
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: key districts and landmarks of Minsk | Statement: [Maskoŭskaja line, servesLandmarks, key districts and landmarks of Minsk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesLandmarks Context triple: [Maskoŭskaja line, servesLandmarks, key districts and landmarks of Minsk]
-
A.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
-
B.
isLandmarkFor
chosen
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
C.
servesAttraction
Indicates that one entity functions as or provides a service that supports or enhances the experience of a particular attraction.
-
D.
isSocialLandmark
Indicates that a place functions as a notable social gathering point or reference location within a community or area.
-
E.
cityLandmarkID
Indicates that a specific landmark is uniquely identified as being located within a particular city.
- 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_69f224cb08908190ba71ad9aa87518ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
Created at: April 29, 2026, 9 p.m.