Triple
T28574475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cochrane–Kirkland Lake |
E723199
|
entity |
| Predicate | languageOfServiceArea |
P99318
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Cochrane–Kirkland Lake, languageOfServiceArea, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfServiceArea Context triple: [Cochrane–Kirkland Lake, languageOfServiceArea, English]
-
A.
currentLanguageOfServices
chosen
Indicates that a specified language is the one presently used to provide or deliver certain services.
-
B.
languageOfProvision
Indicates the language in which a provision, such as a legal or contractual clause, is written or officially expressed.
-
C.
languageOfCoverage
Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
-
D.
serviceBranchLanguage
Indicates the language or languages used or officially recognized by a particular branch of a service (such as a military or organizational branch).
-
E.
languageArea
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
- 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_69f01d7e97708190ae9e77ee66a68abd |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
Created at: April 28, 2026, 4:11 a.m.