Triple
T4349592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen’s Stand |
E97988
|
entity |
| Predicate | hasTypeOfSeating |
P48161
|
FINISHED |
| Object | tiered seating |
—
|
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: tiered seating | Statement: [Queen’s Stand, hasTypeOfSeating, tiered seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfSeating Context triple: [Queen’s Stand, hasTypeOfSeating, tiered seating]
-
A.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
B.
hasBoxSeating
Indicates that an entity provides or includes box seating as a type of seating arrangement.
-
C.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
D.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
E.
classesOfSeats
chosen
Indicates the different categories or types of seats associated with something, such as a venue, vehicle, or event.
- 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351a840248190b88c8a7be9158d25 |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:15 p.m.