Triple
T25970023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pirogovskaya Embankment |
E645778
|
entity |
| Predicate | hasTypeOfLandmarks |
P95089
|
FINISHED |
| Object | architectural monuments |
—
|
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: architectural monuments | Statement: [Pirogovskaya Embankment, hasTypeOfLandmarks, architectural monuments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfLandmarks Context triple: [Pirogovskaya Embankment, hasTypeOfLandmarks, architectural monuments]
-
A.
hasLandmarkProperty
Indicates that something possesses a notable or defining landmark-related characteristic or feature.
-
B.
isLandmarkFor
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.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
-
D.
typeOfLandmark
chosen
Indicates the specific category or kind of landmark that an entity belongs to (e.g., monument, natural feature, building).
-
E.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
- 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_69e77e8768648190b27bb578f14bcb88 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 22, 2026, 8:50 a.m.