Triple
T24637752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Millennium Flood |
E609858
|
entity |
| Predicate | countryWithHighestImpact |
P47514
|
FINISHED |
| Object | Poland |
—
|
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: Poland | Statement: [Millennium Flood, countryWithHighestImpact, Poland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryWithHighestImpact Context triple: [Millennium Flood, countryWithHighestImpact, Poland]
-
A.
countryWithSignificantPopulation
Indicates that a country has a notably large or impactful number of people, relative to some defined threshold or comparison set.
-
B.
countryOfNotableSuccess
Indicates the country in which an entity achieved notable success or recognition.
-
C.
countryInfluence
Indicates the degree to which one country affects or shapes the policies, decisions, or conditions within another country or in the international arena.
-
D.
countrySignificance
Indicates the degree of importance, influence, or relevance that one country holds in relation to another entity or context.
-
E.
countryWithLargestShare
chosen
Indicates that one entity is the country possessing the greatest proportion or share of a specified quantity, resource, or measure compared to all other countries in the given context.
- 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_69e2c4d28f848190ac38c400060e943d |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be064ff88190b5d9e5ec75a41242 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:33 a.m.