Triple
T36800579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Continent |
E909309
|
entity |
| Predicate | typicalReferenceLanguage |
P25852
|
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: [the Continent, typicalReferenceLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalReferenceLanguage Context triple: [the Continent, typicalReferenceLanguage, English]
-
A.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
B.
typicalLanguageOfReadings
chosen
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
C.
refersToLanguageSpokenIn
Indicates that one entity designates or mentions the language that is spoken in another entity (such as a place or region).
-
D.
canonicalLanguage
Indicates that one entity is the officially recognized or standard language associated with another entity.
-
E.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
- 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.