Triple
T1222387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Youngstown |
E26250
|
entity |
| Predicate | distanceToLakeErie |
P25985
|
FINISHED |
| Object | about 65 miles south of Lake Erie |
—
|
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: about 65 miles south of Lake Erie | Statement: [Youngstown, distanceToLakeErie, about 65 miles south of Lake Erie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLakeErie Context triple: [Youngstown, distanceToLakeErie, about 65 miles south of Lake Erie]
-
A.
distanceFromToronto
Indicates the spatial distance between a given entity and the location of Toronto.
-
B.
distanceToToronto
Indicates the spatial distance between a given entity’s location and the city of Toronto.
-
C.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
-
D.
distanceFromWaterloo
Indicates the spatial distance between a given location and Waterloo.
-
E.
distanceToOttawa
Indicates the spatial distance between a given entity’s location and the city of Ottawa.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be21a2bc819094b47580d7c5cdf8 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd3140688190ac6e24de157fd61e |
completed | March 1, 2026, 10:26 p.m. |
Created at: March 1, 2026, 7:47 p.m.