Triple
T16234697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guangzhou Opera House |
E394075
|
entity |
| Predicate | seatingCapacityOfMainHall |
P72212
|
FINISHED |
| Object | about 1800 |
—
|
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 1800 | Statement: [Guangzhou Opera House, seatingCapacityOfMainHall, about 1800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatingCapacityOfMainHall Context triple: [Guangzhou Opera House, seatingCapacityOfMainHall, about 1800]
-
A.
mainHallCapacity
chosen
Indicates the maximum number of people that the main hall can accommodate at one time.
-
B.
hasMainHall
Indicates that an entity possesses or includes a primary or central hall as a significant internal space.
-
C.
hasMainHallType
Indicates the specific category or kind of main hall associated with an entity.
-
D.
mainHallHeight
Indicates the height measurement of a building’s main hall.
-
E.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24559af48819092e4b466778b07e2 |
completed | April 17, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.