Triple
T33348327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mizuho Rugby Stadium |
E853860
|
entity |
| Predicate | hasSeatingCategory |
P9547
|
FINISHED |
| Object | main stand |
—
|
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: main stand | Statement: [Mizuho Rugby Stadium, hasSeatingCategory, main stand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingCategory Context triple: [Mizuho Rugby Stadium, hasSeatingCategory, main stand]
-
A.
hasSeatingClassification
Indicates that an entity is assigned a specific type or category of seating arrangement or capacity.
-
B.
hasSeatingCapacityCategory
Indicates the classification of an entity based on the range or category of how many people it can seat.
-
C.
seatCategory
chosen
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
D.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
E.
hasPrioritySeating
Indicates that one entity provides or designates reserved or preferential seating for another entity.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff7bc112088190851501fb2a16103d |
completed | May 9, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69ff7b45507c81909753866ad733601a |
completed | May 9, 2026, 6:21 p.m. |
Created at: May 1, 2026, 1:34 a.m.