Triple
T9407966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northeastern North America |
E226632
|
entity |
| Predicate | hasDominantLanguages |
P53040
|
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: [Northeastern North America, hasDominantLanguages, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDominantLanguages Context triple: [Northeastern North America, hasDominantLanguages, English]
-
A.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
B.
hasRepresentativeLanguage
chosen
Indicates that an entity is associated with a language that serves as its primary or officially recognized means of representation or communication.
-
C.
dominantMediaLanguage
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
-
D.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
E.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5252b3fc8190b0808a10987728c8 |
completed | April 1, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.