Triple
T2201558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biblioteca Palafoxiana |
E50499
|
entity |
| Predicate | hasApproximateNumberOfItems |
P20367
|
FINISHED |
| Object | over 40,000 volumes |
—
|
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: over 40,000 volumes | Statement: [Biblioteca Palafoxiana, hasApproximateNumberOfItems, over 40,000 volumes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfItems Context triple: [Biblioteca Palafoxiana, hasApproximateNumberOfItems, over 40,000 volumes]
-
A.
hasApproximateMemberCount
chosen
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
B.
hasPageCountApprox
Indicates that an entity is associated with an approximate or estimated number of pages, rather than an exact page count.
-
C.
hasApproximateExtent
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
-
D.
hasApproximateVendorCount
Indicates that an entity is associated with an estimated or non-exact number of vendors.
-
E.
hasApproximateEnd
Indicates that an entity’s end point, time, or boundary is known only approximately rather than precisely.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa1b41c8190b0f7467d0dcdfbcd |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.