Triple
T28159471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Спасо-Преображенский монастырь |
E714849
|
entity |
| Predicate | типПамятника |
P25584
|
FINISHED |
| Object | памятник истории |
—
|
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: памятник истории | Statement: [Спасо-Преображенский монастырь, типПамятника, памятник истории]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: типПамятника Context triple: [Спасо-Преображенский монастырь, типПамятника, памятник истории]
-
A.
monumentType
chosen
Indicates the specific kind or category of monument that an entity is classified as.
-
B.
memorialType
Indicates the specific kind or category of memorial associated with an entity (e.g., plaque, statue, monument).
-
C.
typeOfLandmark
Indicates the specific category or kind of landmark that an entity belongs to (e.g., monument, natural feature, building).
-
D.
monumentSubject
Indicates that the subject serves as the monument or commemorative structure associated with another entity.
-
E.
monumentDepicts
Indicates that a monument visually represents, portrays, or is dedicated to a particular person, event, concept, or object.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f643ed0b7481908cf25f3afec0a61d |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641def1e88190a05bf865ced78b23 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 10:05 p.m.