Triple
T6581217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windows-1252 |
E157300
|
entity |
| Predicate | codePageNumber |
P71604
|
FINISHED |
| Object | 1252 |
—
|
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: 1252 | Statement: [Windows-1252, codePageNumber, 1252]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codePageNumber Context triple: [Windows-1252, codePageNumber, 1252]
-
A.
chapterNumber
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
B.
hasPageCountApprox
Indicates that an entity is associated with an approximate or estimated number of pages, rather than an exact page count.
-
C.
pages
Indicates that one entity consists of or contains a certain number of pages, or that a specific page-related attribute is associated with it.
-
D.
hasPageRangeInMushaf
Indicates that a text segment spans a specific range of pages within a particular mushaf (written copy of the Quran).
-
E.
pageCountFirstEdition
Indicates the number of pages contained in the first edition of an item.
- 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_69c6882b3a108190b3a9eb343ae4162c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6c07bb434819096ec3e3b966042a5 |
completed | March 27, 2026, 5:38 p.m. |
Created at: March 27, 2026, 1:54 p.m.