Triple
T959167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supreme Court Building |
E20694
|
entity |
| Predicate | hasCourtroomSeatingCapacityApprox |
P2491
|
FINISHED |
| Object | 400 |
—
|
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: 400 | Statement: [Supreme Court Building, hasCourtroomSeatingCapacityApprox, 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourtroomSeatingCapacityApprox Context triple: [Supreme Court Building, hasCourtroomSeatingCapacityApprox, 400]
-
A.
seatingCapacity
chosen
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
B.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
C.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
D.
courtyardCapacity
Indicates the maximum number of entities that can be accommodated in a courtyard at the same time.
-
E.
plenaryChamberCapacity
Indicates the seating capacity of the main plenary chamber where formal sessions or assemblies are held.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3fc94ec8190b55c6cdf3a37d6b5 |
completed | March 1, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a18ecc8190883f6206fe3b0fb6 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.