Triple
T6310051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montréal-Ouest |
E141475
|
entity |
| Predicate | otherOfficialLanguage |
P5601
|
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: [Montréal-Ouest, otherOfficialLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherOfficialLanguage Context triple: [Montréal-Ouest, otherOfficialLanguage, English]
-
A.
additionalOfficialLanguage
chosen
Indicates that an entity has another language, beyond its primary one, that holds official or formally recognized status.
-
B.
previousOfficialLanguage
Indicates that one language formerly held official status in a country, region, or organization before being replaced or losing that status.
-
C.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
-
D.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
E.
oneOfSixOfficialLanguagesOf
Indicates that a language is one of the six officially recognized languages of a particular organization, institution, or entity.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0648074b081908ba661651ba705a7 |
completed | March 22, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.