Triple
T21979757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Town of Szczecin |
E542804
|
entity |
| Predicate | hasCobbledStreets |
P146140
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Old Town of Szczecin, hasCobbledStreets, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCobbledStreets Context triple: [Old Town of Szczecin, hasCobbledStreets, true]
-
A.
hasNumberOfStreets
Indicates the relationship that specifies how many streets are associated with or contained within a given entity.
-
B.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
-
C.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
D.
hasHistoricStreet
Indicates that an entity is associated with or located on a street that has recognized historical significance.
-
E.
betweenStreets
Indicates that one location is situated between two specified streets, typically along a road segment bounded by those streets.
- F. None of above. chosen
Provenance (4 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_69e0c48070988190909db97667b9a0ac |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1248bdd88819098bfeca550608f14 |
completed | April 28, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:03 p.m.