Triple
T15693078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old City district (Varousi) |
E380381
|
entity |
| Predicate | hasTypeOfStreets |
P44319
|
FINISHED |
| Object | cobbled streets |
—
|
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: cobbled streets | Statement: [Old City district (Varousi), hasTypeOfStreets, cobbled streets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfStreets Context triple: [Old City district (Varousi), hasTypeOfStreets, cobbled streets]
-
A.
hasSideStreetType
Indicates that an entity (such as a street or road segment) is associated with a specific type or classification of side street.
-
B.
hasNumberOfStreets
Indicates the relationship that specifies how many streets are associated with or contained within a given entity.
-
C.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
D.
streetOrAreaType
chosen
Indicates the specific kind or classification of a street or area (such as avenue, boulevard, district, or zone) associated with an entity.
-
E.
hasStreetLevel
Indicates that something is located at, accessible from, or directly associated with the street level of a building or area.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0051d639481909a10614e8f83e659 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:44 a.m.