Triple
T26625126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Mitch |
E668319
|
entity |
| Predicate | landfallTypeInHonduras |
P142575
|
FINISHED |
| Object | Category 1 hurricane at landfall |
—
|
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: Category 1 hurricane at landfall | Statement: [Hurricane Mitch, landfallTypeInHonduras, Category 1 hurricane at landfall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landfallTypeInHonduras Context triple: [Hurricane Mitch, landfallTypeInHonduras, Category 1 hurricane at landfall]
-
A.
stormTypeAtLandfall
chosen
Indicates the classification or category of a storm at the specific time and location where it makes landfall.
-
B.
landfallLocation
Indicates the geographic location where a storm or similar weather system first makes landfall.
-
C.
landfallIntensity
Indicates the strength or magnitude of a storm system at the time and location where it first makes landfall.
-
D.
firstLandfallBy
Indicates the location or entity where something (typically a storm, traveler, or object) initially makes landfall or first arrives from a journey over water or air.
-
E.
landfallEffect
Indicates the impact or consequences that occur when a storm or similar weather system moves from water onto land.
- 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_69ee9cff507c819092b95bf7219a702e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f615e831d88190bbc27081f6ce15b2 |
completed | May 2, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f60b8bb0d08190ab5a9a2a8847c6f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 2:22 a.m.