Triple
T25671861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreal Metro Blue Line extension |
E643698
|
entity |
| Predicate | hasLanguageOfPlanningDocuments |
P42366
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Montreal Metro Blue Line extension, hasLanguageOfPlanningDocuments, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfPlanningDocuments Context triple: [Montreal Metro Blue Line extension, hasLanguageOfPlanningDocuments, French]
-
A.
hasLanguageOfOfficialPlanningDocuments
chosen
Indicates that an entity uses a specified language in its official planning documents.
-
B.
hasLinguisticDocumentation
Indicates that there exists recorded linguistic information or documentation about the language or linguistic properties of the subject.
-
C.
hasLanguageOfMission
Indicates that an entity (such as a mission or project) is associated with a specific language used for its communication, documentation, or operation.
-
D.
hasRepresentativeLanguage
Indicates that an entity is associated with a language that serves as its primary or officially recognized means of representation or communication.
-
E.
isScheduledLanguageOf
Indicates that a particular language is officially planned or designated to be used for a specific event, program, or context.
- 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_69e77e7f69808190ad27df1006f6037a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 21, 2026, 7:29 p.m.