Triple
T8358468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messerschmitt Kabinenroller |
E196738
|
entity |
| Predicate | seatArrangement |
P16826
|
FINISHED |
| Object | tandem 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: tandem seating | Statement: [Messerschmitt Kabinenroller, seatArrangement, tandem seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatArrangement Context triple: [Messerschmitt Kabinenroller, seatArrangement, tandem seating]
-
A.
seatingConfiguration
chosen
Indicates how seats are arranged or organized relative to each other in a given context.
-
B.
seatNotationSystem
Indicates the system or convention used to label, number, or otherwise denote seats within a venue or vehicle.
-
C.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
D.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
E.
seatSince
Indicates that an entity has held a particular seat, position, or place continuously since a specified point in time.
- 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_69ca82f08b348190bfb7881944bbff6f |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb806fa5c88190b23b6b3ee9d6ec6d |
completed | March 31, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69cb70ca25548190b0f90c5384e3fb3c |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:59 p.m.