Triple
T37826956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 United States House of Representatives elections |
E943086
|
entity |
| Predicate | languageOfArticle |
P31857
|
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: [2016 United States House of Representatives elections, languageOfArticle, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfArticle Context triple: [2016 United States House of Representatives elections, languageOfArticle, English]
-
A.
languageOfAuthor
Indicates the language in which an author writes or has written their works.
-
B.
languageOfManuscript
Indicates the language in which a given manuscript is written.
-
C.
contentLanguage
chosen
Indicates the language in which the content is expressed or intended to be understood.
-
D.
languageOfLitury
Indicates the language in which a liturgy or formal religious worship service is conducted.
-
E.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
- 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_69f76eea4c8c8190a335aed5955cf2db |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a01bb06422c819095bb42f6f3a0e801 |
completed | May 11, 2026, 11:18 a.m. |
| PD | Predicate disambiguation | batch_6a01b9991c348190ac49b65ea2fd86ed |
completed | May 11, 2026, 11:12 a.m. |
Created at: May 3, 2026, 4:19 p.m.