Triple
T21235098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Symphony Hall |
E523321
|
entity |
| Predicate | seatingCapacityChamberHall |
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: [Shanghai Symphony Hall, seatingCapacityChamberHall, 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatingCapacityChamberHall Context triple: [Shanghai Symphony Hall, seatingCapacityChamberHall, 400]
-
A.
mainHallCapacity
Indicates the maximum number of people that the main hall can accommodate at one time.
-
B.
plenaryChamberCapacity
Indicates the seating capacity of the main plenary chamber where formal sessions or assemblies are held.
-
C.
seatingCapacity
chosen
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
D.
roomCapacity
Indicates the maximum number of people or occupants that a room is designed or allowed to hold.
-
E.
hasSmallHallCapacity
Indicates that the capacity of a hall is below a defined threshold, classifying it as small.
- 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_69e0b512ad94819087942b2ed925185f |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7351f0e988190bb77b598cb8a9532 |
completed | April 21, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e5f60e1a888190ba75e2e900270a4e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:46 p.m.