Triple
T17989196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lethbridge Airport |
E430322
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Lethbridge |
—
|
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: Lethbridge | Statement: [Lethbridge Airport, serves, Lethbridge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lethbridge Context triple: [Lethbridge Airport, serves, Lethbridge]
-
A.
Lethbridge
chosen
Lethbridge is a mid-sized city in southern Alberta, Canada, known for its coulee landscapes, windy climate, and role as a regional commercial and educational hub.
-
B.
Medicine Hat
Medicine Hat is a mid-sized city in southeastern Alberta, Canada, known for its natural gas reserves and nickname "The Gas City."
-
C.
Kalgary
Kalgary is a small unincorporated rural community located in Crosby County in the U.S. state of Texas.
-
D.
Stettler
Stettler is a Swiss surname most notably associated with painter and art educator Martha Stettler.
-
E.
Stettler
Stettler is a small town in central Alberta, Canada, known for its agricultural roots and heritage railway attractions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29e47a88190be58b79c73d3e652 |
completed | April 19, 2026, 10:46 a.m. |
Created at: April 10, 2026, 10:23 a.m.