Triple
T5441682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SnowCastle of Kemi |
E122147
|
entity |
| Predicate | rebuildFrequency |
P44073
|
FINISHED |
| Object | annually |
—
|
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: annually | Statement: [SnowCastle of Kemi, rebuildFrequency, annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rebuildFrequency Context triple: [SnowCastle of Kemi, rebuildFrequency, annually]
-
A.
rebuildPeriod
chosen
Indicates the time span during which something is reconstructed or restored after damage, failure, or decommissioning.
-
B.
rebuild
Indicates restoring or constructing again something that was previously built, often after damage, destruction, or significant alteration.
-
C.
rebuiltOn
Indicates that one entity has been reconstructed, restored, or built again on, over, or using the foundation, structure, or basis of another entity.
-
D.
rebuiltMultipleTimes
Indicates that the same entity has been reconstructed or restored on more than one separate occasion.
-
E.
replacedFrequency
Indicates how often one entity is substituted for or takes the place of another over a given period.
- 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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd922f66bc8190b7d47fd68d2fcf2e |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd919aeb048190b786f814177d6cd9 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.