Triple
T11509728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pakistani passports |
E272876
|
entity |
| Predicate | pageCountVariant |
P1468
|
FINISHED |
| Object | 36 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: 36 pages | Statement: [Pakistani passports, pageCountVariant, 36 pages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pageCountVariant Context triple: [Pakistani passports, pageCountVariant, 36 pages]
-
A.
hasPageCountApprox
Indicates that an entity is associated with an approximate or estimated number of pages, rather than an exact page count.
-
B.
codePageNumber
Indicates the specific page number within a code document or code listing where something is located or referenced.
-
C.
pageSize
Indicates the size or amount of content (such as items, records, or data) that is included or displayed on a single page.
-
D.
pageCountFirstEdition
Indicates the number of pages contained in the first edition of an item.
-
E.
pages
chosen
Indicates that one entity consists of or contains a certain number of pages, or that a specific page-related attribute is associated with it.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d86db65eb081908613a1002c6a4fb4 |
completed | April 10, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.