Triple
T4565766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Capital Region of Canada |
E121904
|
entity |
| Predicate | hasBilingualCharacter |
P21622
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [National Capital Region of Canada, hasBilingualCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBilingualCharacter Context triple: [National Capital Region of Canada, hasBilingualCharacter, true]
-
A.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
B.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
C.
isBilingualRegion
chosen
Indicates that a region officially uses two languages or has two predominant languages in regular use.
-
D.
hasUnicodeStatus
Indicates that a given entity has a particular Unicode-related classification or status (such as assigned, reserved, deprecated, or noncharacter) within the Unicode standard.
-
E.
bilingualName
Indicates that an entity has a name expressed in two different languages, linking the entity to its bilingual designation.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589cde9081909b84186d700fc463 |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd52254c648190a5144cfe8fa7e409 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.