Triple
T14304390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ylivieska |
E354653
|
entity |
| Predicate | churchBurnedDown |
P78149
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Ylivieska, churchBurnedDown, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: churchBurnedDown Context triple: [Ylivieska, churchBurnedDown, 2016]
-
A.
houseBurned
Indicates that a house has been destroyed or significantly damaged by fire.
-
B.
originalChurchDestroyed
chosen
Indicates that the initially established church building was demolished or ceased to exist, typically due to destruction rather than relocation or replacement.
-
C.
firstBuildingDestroyedByFire
Indicates that the first building in a given context was destroyed as a result of a fire.
-
D.
townHallDemolishedIn
Indicates that a town hall building was demolished in the specified location or during the specified event or time period.
-
E.
hasReconstructedChurch
Indicates that an entity has rebuilt or restored a church, typically after damage, destruction, or disuse.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85afabe48190926d6098047f4bcf |
completed | April 14, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:12 a.m.