Triple
T1605062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Party |
E34482
|
entity |
| Predicate | officialLanguageUse |
P30223
|
FINISHED |
| Object | English |
E211
|
NE 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: [National Party, officialLanguageUse, English]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: English Context triple: [National Party, officialLanguageUse, English]
-
A.
English
chosen
English is a widely spoken West Germanic language that serves as a global lingua franca in education, business, science, and international communication.
-
B.
ENG
ENG is the three-letter FIFA country code used to represent the England national football team in international competitions and official records.
-
C.
English American
English American refers to a U.S. resident or citizen of English ancestry, whose heritage traces back to settlers and immigrants from England.
-
D.
Oxford English
Oxford English is a prestigious accent of British English traditionally associated with educated speakers and often used as a standard in broadcasting and formal contexts.
-
E.
English (film)
English (film) is a cinematic work produced in the English language, likely featuring the character Rita Vrataski.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa61df32a88190a7e823a77bdcc84a |
completed | March 6, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad51bcdebc81909520786c560598b6 |
completed | March 8, 2026, 10:38 a.m. |
Created at: March 4, 2026, 7:28 p.m.