Triple
T29878379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McDonnell Douglas MD-88 |
E758806
|
entity |
| Predicate | passengerCabinConfiguration |
P16894
|
FINISHED |
| Object | single-aisle |
—
|
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: single-aisle | Statement: [McDonnell Douglas MD-88, passengerCabinConfiguration, single-aisle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerCabinConfiguration Context triple: [McDonnell Douglas MD-88, passengerCabinConfiguration, single-aisle]
-
A.
cabinConfiguration
chosen
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
B.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
C.
servesCabinClass
Indicates that a service provider (such as an airline or flight) offers or is available to a specified cabin class (e.g., economy, business, first).
-
D.
cabinClassAbove
Indicates that one cabin class is ranked higher or more premium than another in a class hierarchy.
-
E.
roomConfiguration
Indicates how elements within a room are arranged or organized relative to each other.
- 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_69f2245d0d7081909e37ee328542bcd7 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6bbf6e33c819086e5176d64e7a614 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
Created at: April 29, 2026, 5:56 p.m.