Triple
T1509210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Notes on the State of Virginia |
E33974
|
entity |
| Predicate | firstEditionLanguage |
P29379
|
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: [Notes on the State of Virginia, firstEditionLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstEditionLanguage Context triple: [Notes on the State of Virginia, firstEditionLanguage, English]
-
A.
firstEditionType
Indicates that an entity is classified as a first edition of a work, specifying the type or category of that first edition.
-
B.
languageOfOfficialEditions
Indicates the language in which the official editions or versions of a work, document, or publication are produced or authorized.
-
C.
isbnFirstEnglishEdition
Indicates that the object is the ISBN identifier corresponding to the first English-language edition of the subject work.
-
D.
originalPublicationLanguageVariant
Indicates that one language is a specific variant or version of the language in which a work was originally published.
-
E.
firstEditionPublicationYear
Indicates the year in which an entity’s first edition was originally published.
- F. None of above. chosen
Provenance (4 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a8e2dd93dc8190a78443900e8d5564 |
completed | March 5, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a88728c150819095cdcdbfcabf4249 |
completed | March 4, 2026, 7:25 p.m. |
| PDg | Predicate description generation | batch_69a8e2dbc848819084eb0d50189fa967 |
completed | March 5, 2026, 1:56 a.m. |
Created at: March 4, 2026, 7:24 p.m.