Triple
T1896212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boston Cooking-School Cook Book |
E41987
|
entity |
| Predicate | firstEditionPageCount |
P17137
|
FINISHED |
| Object | approximately 600 pages |
—
|
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: approximately 600 pages | Statement: [The Boston Cooking-School Cook Book, firstEditionPageCount, approximately 600 pages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstEditionPageCount Context triple: [The Boston Cooking-School Cook Book, firstEditionPageCount, approximately 600 pages]
-
A.
pageCountFirstEdition
chosen
Indicates the number of pages contained in the first edition of an item.
-
B.
firstEditionType
Indicates that an entity is classified as a first edition of a work, specifying the type or category of that first edition.
-
C.
firstEditionPrintRun
Indicates the initial quantity of copies produced when a work is printed in its first published edition.
-
D.
firstEditionVolumes
Indicates that the subject is a work or publication and the object is the number of volumes in its first edition.
-
E.
firstEditionPublicationYear
Indicates the year in which an entity’s first edition was originally published.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb16d6674819084a891e3bf23bd83 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe7e7e88190b58c0df59187c0c2 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.