Triple
T5471674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyumri |
E122847
|
entity |
| Predicate | earthquakeImpact |
P5296
|
FINISHED |
| Object | severe destruction and loss of life |
—
|
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: severe destruction and loss of life | Statement: [Gyumri, earthquakeImpact, severe destruction and loss of life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earthquakeImpact Context triple: [Gyumri, earthquakeImpact, severe destruction and loss of life]
-
A.
populationImpact2010Earthquake
Indicates the effect or consequences that the 2010 earthquake had on a population, such as changes in size, distribution, or demographic characteristics.
-
B.
earthquakeType
Indicates the specific classification or category of an earthquake based on its characteristics or cause.
-
C.
earthquakeHazardLevel
Indicates the assessed degree of risk or potential impact from earthquakes associated with a given location or entity.
-
D.
hasEarthquakes
Indicates that the specified location or region experiences one or more earthquakes.
-
E.
facedMajorEarthquake
chosen
Indicates that an entity has experienced or been subjected to a significant or severe earthquake event.
- 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_69bd46459ff48190823377457bcf7128 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd921d02188190b5c1eee7205ea88e |
completed | March 20, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.