Triple
T19828065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Bridge in Vilnius |
E476379
|
entity |
| Predicate | hasSculpturalGroupsCount |
P22479
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Green Bridge in Vilnius, hasSculpturalGroupsCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSculpturalGroupsCount Context triple: [Green Bridge in Vilnius, hasSculpturalGroupsCount, 4]
-
A.
numberOfSculptures
chosen
Indicates the quantity of sculptures associated with a given entity or context.
-
B.
hasSculpturalFigures
Indicates that something includes or features three-dimensional sculpted figures as part of its form or decoration.
-
C.
hasSculptureType
Indicates that an entity is associated with a sculpture and specifies the type or category of that sculpture.
-
D.
numberOfPaintedSculptures
Indicates the quantity of sculptures that have been painted in a given context or collection.
-
E.
hasSculpturalProgram
Indicates that an entity features or is associated with a specific sculptural decoration scheme or program.
- 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e656cc0f2c81908137caa4c2087027 |
completed | April 20, 2026, 4:39 p.m. |
| PD | Predicate disambiguation | batch_69e5305bda388190a23b7191768107b1 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.