Triple
T24635953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wei-Wu-Ying Opera House |
E609810
|
entity |
| Predicate | seatingCapacityOfOperaHouse |
P128833
|
FINISHED |
| Object | about 2236 |
—
|
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: about 2236 | Statement: [Wei-Wu-Ying Opera House, seatingCapacityOfOperaHouse, about 2236]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatingCapacityOfOperaHouse Context triple: [Wei-Wu-Ying Opera House, seatingCapacityOfOperaHouse, about 2236]
-
A.
operaHouseCapacity
chosen
Indicates the maximum number of people that an opera house is designed or allowed to accommodate.
-
B.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
C.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
D.
operaHouseType
Indicates the specific kind or classification of an opera house associated with an entity.
-
E.
hasOrchestraPitCapacity
Indicates the number of people that can be accommodated in the orchestra pit associated with a venue or performance space.
- 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_69e2c4d28f848190ac38c400060e943d |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be064ff88190b5d9e5ec75a41242 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:32 a.m.