Triple
T19828081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Bridge in Vilnius |
E476379
|
entity |
| Predicate | hasPreviousStructureDestroyedIn |
P43527
|
FINISHED |
| Object | 1944 |
—
|
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: 1944 | Statement: [Green Bridge in Vilnius, hasPreviousStructureDestroyedIn, 1944]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreviousStructureDestroyedIn Context triple: [Green Bridge in Vilnius, hasPreviousStructureDestroyedIn, 1944]
-
A.
hasStructureHistory
Indicates that there exists a record or account detailing the past states, changes, or development of a structure over time.
-
B.
hasFormerBuilding
Indicates that an entity previously occupied or used a different building, which is identified as its former building.
-
C.
wasDestroyedOrTransformed
chosen
Indicates that an entity ceased to exist in its original form due to being either destroyed or fundamentally transformed.
-
D.
previousStructure
Indicates that one structure directly precedes another in a defined sequence or configuration.
-
E.
hasPredecessorStructureFrom
Indicates that one structure existed or was established before another structure in a sequential or developmental order.
- 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.