Triple
T669144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Sea flood of 1953 |
E12932
|
entity |
| Predicate | deathsInUnitedKingdom |
P1785
|
FINISHED |
| Object | over 300 |
—
|
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: over 300 | Statement: [North Sea flood of 1953, deathsInUnitedKingdom, over 300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathsInUnitedKingdom Context triple: [North Sea flood of 1953, deathsInUnitedKingdom, over 300]
-
A.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
B.
countryOfDeath
Indicates the country in which an entity (typically a person) died.
-
C.
deathToll
chosen
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
D.
notableDeath
Indicates that an entity’s death is considered significant or noteworthy in some context.
-
E.
traditionallyDiedIn
Indicates that, according to tradition or customary accounts (rather than strictly verified historical evidence), one entity is said to have died in the location or context of another entity.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49ffbe09881909b547a52a6b34c7f |
completed | March 1, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69a49d18942c819083b3d1887e505900 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.