Triple
T25432783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diophantus of Alexandria |
E637301
|
entity |
| Predicate | originalBooksCount |
P5481
|
FINISHED |
| Object | thirteen books of Arithmetica |
—
|
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: thirteen books of Arithmetica | Statement: [Diophantus of Alexandria, originalBooksCount, thirteen books of Arithmetica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalBooksCount Context triple: [Diophantus of Alexandria, originalBooksCount, thirteen books of Arithmetica]
-
A.
numberOfBooks
chosen
Indicates the quantity of books associated with a given entity.
-
B.
intendedNumberOfBooks
Indicates the number of books that an agent plans or aims to have, produce, read, or otherwise be associated with, as opposed to the number actually realized.
-
C.
numberOfCompletedBooks
Indicates the total count of books that an entity has finished reading or completing.
-
D.
bookNumberInCollection
Indicates the specific numerical position assigned to a book within a particular collection.
-
E.
numberOfWorks
Indicates the total count of works associated with a given entity.
- 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 21, 2026, 1:58 p.m.