Triple
T24502274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 Southeast Europe floods |
E617965
|
entity |
| Predicate | countryMostSeverelyAffected |
P53564
|
FINISHED |
| Object | Bosnia and Herzegovina |
—
|
NE NERFINISHED |
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: Bosnia and Herzegovina | Statement: [2014 Southeast Europe floods, countryMostSeverelyAffected, Bosnia and Herzegovina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryMostSeverelyAffected Context triple: [2014 Southeast Europe floods, countryMostSeverelyAffected, Bosnia and Herzegovina]
-
A.
countryMostVictimsFrom
chosen
Indicates the country from which the largest number of victims in a given event, situation, or context originate.
-
B.
affectedCountry
Indicates that a particular country is impacted or influenced by an event, action, or condition.
-
C.
countryWithSignificantPopulation
Indicates that a country has a notably large or impactful number of people, relative to some defined threshold or comparison set.
-
D.
isMostPopulousRegionOf
Indicates that a region has the largest population among all regions within the specified larger area or entity.
-
E.
countryWhereOccurred
Indicates the country in which a particular event, action, or occurrence took place.
- 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_69e2d7f682108190a1a7ca5fd485ee8a |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:23 a.m.