Triple
T18599368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hagley Oval |
E454577
|
entity |
| Predicate | hasTemporarySeatingCapacity |
P132734
|
FINISHED |
| Object | 20000 |
—
|
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: 20000 | Statement: [Hagley Oval, hasTemporarySeatingCapacity, 20000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporarySeatingCapacity Context triple: [Hagley Oval, hasTemporarySeatingCapacity, 20000]
-
A.
reducedSeatingCapacityFrom
Indicates that an entity has a smaller seating capacity than it previously had, with the prior capacity specified by the related entity.
-
B.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
C.
hasSeatingCapacityCategory
Indicates the classification of an entity based on the range or category of how many people it can seat.
-
D.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
E.
hasReservedSeats
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
- F. None of above. chosen
Provenance (4 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5474f1d548190b74408eabd396344 |
completed | April 19, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:45 a.m.