Triple
T19737571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khrushchyovka mass housing |
E474026
|
entity |
| Predicate | typicalApartmentLayout |
P67991
|
FINISHED |
| Object | one-bedroom apartments |
—
|
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: one-bedroom apartments | Statement: [Khrushchyovka mass housing, typicalApartmentLayout, one-bedroom apartments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalApartmentLayout Context triple: [Khrushchyovka mass housing, typicalApartmentLayout, one-bedroom apartments]
-
A.
typicalInterior
Indicates that one entity is the usual or characteristic interior of another entity.
-
B.
typicalUnitConfiguration
chosen
Indicates the standard or commonly used arrangement, composition, or setup of a unit in a given context.
-
C.
typicalUnitType
Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
-
D.
typicalHouse
Indicates that something is a standard or representative example of a house in terms of its usual features, structure, or characteristics.
-
E.
spaceType
Indicates the category or kind of physical or conceptual space associated with an entity.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6515ea688819097b6838e6a3b3d4a |
completed | April 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.