Triple
T3289436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polybius’ Histories |
E69064
|
entity |
| Predicate | originalNumberOfBooks |
P5481
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Polybius’ Histories, originalNumberOfBooks, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalNumberOfBooks Context triple: [Polybius’ Histories, originalNumberOfBooks, 40]
-
A.
numberOfBooks
chosen
Indicates the quantity of books associated with a given entity.
-
B.
librarySystemSize
Indicates the overall scale or capacity of a library system, such as the number of branches, items, or resources it encompasses.
-
C.
numberOfBiblicalBooks
Indicates the total count of books contained in a specified version or canon of the Bible.
-
D.
originalNumberOfLanguages
Indicates the initial count of distinct languages associated with an entity before any changes or reductions occur.
-
E.
originalNumberOfMembers
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb05a3e5c819082552a7a911e3230 |
completed | March 8, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69ada421fadc8190b7c7d3c8afd20061 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.