Triple
T4345375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GM Lambda platform |
E97885
|
entity |
| Predicate | numberOfRowsOfSeating |
P25953
|
FINISHED |
| Object | three-row 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: three-row seating | Statement: [GM Lambda platform, numberOfRowsOfSeating, three-row seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRowsOfSeating Context triple: [GM Lambda platform, numberOfRowsOfSeating, three-row seating]
-
A.
numberOfSeatingRows
chosen
Indicates the total count of seating rows associated with an entity, such as a venue, vehicle, or seating area.
-
B.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
C.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
D.
numberOfCommonsSeats
Indicates the number of seats an entity holds or is allocated in the House of Commons.
-
E.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other in a given context.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3518bec408190ba07643bbf7eb632 |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:15 p.m.