Triple
T10181751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodbridge, Ontario |
E236801
|
entity |
| Predicate | commonLanguageSpoken |
P741
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [Woodbridge, Ontario, commonLanguageSpoken, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonLanguageSpoken Context triple: [Woodbridge, Ontario, commonLanguageSpoken, Italian]
-
A.
languagesSpoken
chosen
Indicates that an entity is able to communicate using one or more specified languages.
-
B.
parentLanguage
Indicates that one language is the ancestral or source language from which another language is derived or historically developed.
-
C.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
D.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
E.
spokenPrimarilyOn
Indicates that something (typically a language or dialect) is used mainly for spoken communication in a particular context, region, or group.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded32b91c8190b01ad37b2456080a |
completed | April 2, 2026, 4:14 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:12 p.m.