Triple
T34207721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greenland, Michigan |
E877558
|
entity |
| Predicate | distanceToLakeSuperior |
P205365
|
FINISHED |
| Object | approximately 10–20 miles south of Lake Superior shoreline |
—
|
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 10–20 miles south of Lake Superior shoreline | Statement: [Greenland, Michigan, distanceToLakeSuperior, approximately 10–20 miles south of Lake Superior shoreline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLakeSuperior Context triple: [Greenland, Michigan, distanceToLakeSuperior, approximately 10–20 miles south of Lake Superior shoreline]
-
A.
distanceToLakeErie
Indicates the measured or specified distance between a given entity or location and Lake Erie.
-
B.
distanceToLakeHuronShoreline
Indicates the measured distance between a given location and the shoreline of Lake Huron.
-
C.
distanceToSaranacLake
Indicates the spatial distance between a given entity and Saranac Lake.
-
D.
distanceToWinnipeg
Indicates the spatial distance between a given entity’s location and the city of Winnipeg.
-
E.
distanceToMarquetteInMiles
Indicates the numerical distance, measured in miles, between a given entity’s location and Marquette.
- 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_69f349aff5f0819096275315abea5344 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:55 a.m.