Triple
T35959413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Storm of 1913 |
E1039954
|
entity |
| Predicate | hardestHitLake |
P184283
|
FINISHED |
| Object | Lake Huron |
—
|
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: Lake Huron | Statement: [Great Storm of 1913, hardestHitLake, Lake Huron]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hardestHitLake Context triple: [Great Storm of 1913, hardestHitLake, Lake Huron]
-
A.
isNorthernmostLargeLakeOf
Indicates that a lake is the northernmost among all lakes classified as large within a specified area or set.
-
B.
mostVisitedLakeOf
Indicates that the subject is the lake most frequently visited in relation to the specified entity (such as a region, country, or person).
-
C.
maximumLake
Indicates that the subject entity is the lake with the greatest value (such as size, volume, or another specified measure) among a given set of lakes.
-
D.
mostFamousLakeOf
Indicates that one entity is the most famous or well-known lake associated with, located in, or characterizing another entity (such as a region, country, or city).
-
E.
isLargestInlandLakeIn
Indicates that a lake is the largest inland lake within the specified geographic region or area.
- F. None of above. chosen
Provenance (4 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7ac2210e481909279dade5328825c |
completed | May 3, 2026, 8:12 p.m. |
Created at: May 3, 2026, 4:07 p.m.