Triple
T4341145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stockholm Public Library |
E97580
|
entity |
| Predicate | hasReadingRoomCapacity |
P56142
|
FINISHED |
| Object | hundreds of visitors |
—
|
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: hundreds of visitors | Statement: [Stockholm Public Library, hasReadingRoomCapacity, hundreds of visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReadingRoomCapacity Context triple: [Stockholm Public Library, hasReadingRoomCapacity, hundreds of visitors]
-
A.
hasReadingRoom
Indicates that a place or facility includes a designated reading room area available for use.
-
B.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
C.
hasStandingCapacity
Indicates that an entity is capable of maintaining or supporting a specified condition, function, or load on an ongoing basis.
-
D.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
E.
typicalSeatingCapacityUpperBound
Indicates the maximum number of seats that a venue or vehicle is typically designed or allowed to accommodate under normal conditions.
- 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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35170a6648190a15ffb21640ee478 |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b350d1649881908fa6556d875a8b4d |
completed | March 12, 2026, 11:48 p.m. |
Created at: March 12, 2026, 11:14 p.m.