Triple
T60684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Superior |
E1205
|
entity |
| Predicate | hasShorelineLength |
P1568
|
FINISHED |
| Object | approximately 4,300 kilometers |
—
|
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: approximately 4,300 kilometers | Statement: [Lake Superior, hasShorelineLength, approximately 4,300 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShorelineLength Context triple: [Lake Superior, hasShorelineLength, approximately 4,300 kilometers]
-
A.
shorelineLength
chosen
Indicates the total measured extent of a land area’s boundary where it meets a body of water.
-
B.
hasCoastline
Indicates that a geographic entity is bordered by and directly touches a sea or ocean along part of its boundary.
-
C.
hasCoastlineType
Indicates the specific nature or classification of the coastline associated with a geographic entity.
-
D.
hasCityOnShore
Indicates that a city is located on or directly adjacent to the shore of a body of water.
-
E.
hasCoastlineOn
Indicates that one entity’s coastline borders or is directly adjacent to a specified body of water.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251a1b8ac8190b44be4c3c41e5681 |
completed | Feb. 28, 2026, 2:23 a.m. |
| PD | Predicate disambiguation | batch_69a24ea0bec48190b2af1fb287e9e692 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.