Triple
T13422757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Święty Marcin Street |
E313397
|
entity |
| Predicate | hasNotableTypeOfBuilding |
P50464
|
FINISHED |
| Object | commercial buildings |
—
|
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: commercial buildings | Statement: [Święty Marcin Street, hasNotableTypeOfBuilding, commercial buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableTypeOfBuilding Context triple: [Święty Marcin Street, hasNotableTypeOfBuilding, commercial buildings]
-
A.
containsBuildingType
chosen
Indicates that a location or area includes at least one building of the specified type.
-
B.
containsBuilding
Indicates that one location or area includes a building within its boundaries.
-
C.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
D.
hasBuildingHeightType
Indicates the classification or type used to characterize the height of a building in the relationship.
-
E.
hasMunicipalBuildings
Indicates that a place or jurisdiction possesses one or more buildings used for municipal or local government functions.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaecf13748190ae40c7b95164f914 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:39 p.m.