Triple
T35497572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bormla |
E1025909
|
entity |
| Predicate | hasRebuiltAreas |
P70431
|
FINISHED |
| Object | post–World War II reconstruction |
—
|
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: post–World War II reconstruction | Statement: [Bormla, hasRebuiltAreas, post–World War II reconstruction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRebuiltAreas Context triple: [Bormla, hasRebuiltAreas, post–World War II reconstruction]
-
A.
hasRedevelopedArea
chosen
Indicates that an entity has an area that has been improved, renovated, or rebuilt from its previous state.
-
B.
hasRebuilt
Indicates that an entity has restored, reconstructed, or built again something that previously existed or was damaged or destroyed.
-
C.
hasRebuiltInfrastructure
Indicates that an entity has restored or reconstructed damaged or outdated infrastructure, typically improving or modernizing it in the process.
-
D.
hasReconstructedHouseOf
Indicates that one entity has rebuilt or restored the house that belongs or once belonged to another entity.
-
E.
hasReclaimedMiningAreas
Indicates that an entity possesses or includes areas previously used for mining that have been restored or rehabilitated.
- 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_69f76dfc9c60819089c4217d93922615 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:04 p.m.