Triple
T28907908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teatro Nacional Cervantes |
E733135
|
entity |
| Predicate | hasNumberOfSeatingCapacity |
P63301
|
FINISHED |
| Object | approximately 800 |
—
|
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: approximately 800 | Statement: [Teatro Nacional Cervantes, hasNumberOfSeatingCapacity, approximately 800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSeatingCapacity Context triple: [Teatro Nacional Cervantes, hasNumberOfSeatingCapacity, approximately 800]
-
A.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
B.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
C.
seatCount
chosen
Indicates the number of seats associated with an entity, such as a venue, vehicle, or room.
-
D.
hasSeatingCapacityCategory
Indicates the classification of an entity based on the range or category of how many people it can seat.
-
E.
hasSeatingCapacityWithStanding
Indicates that an entity has a total seating capacity that explicitly includes standing room capacity as part of its overall accommodation.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: April 28, 2026, 8:09 a.m.