Triple
T22480903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tu-204C freighter |
E555759
|
entity |
| Predicate | passengerCabin |
P16894
|
FINISHED |
| Object | removed for cargo use |
—
|
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: removed for cargo use | Statement: [Tu-204C freighter, passengerCabin, removed for cargo use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerCabin Context triple: [Tu-204C freighter, passengerCabin, removed for cargo use]
-
A.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
B.
cabinClassAbove
Indicates that one cabin class is ranked higher or more premium than another in a class hierarchy.
-
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.
cabinClassBelow
Indicates that one entity’s cabin class is ranked lower or less premium than another entity’s cabin class.
-
E.
cabinConfiguration
chosen
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c397b248190b36c2fbfa6489693 |
completed | April 29, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69e898b6eee08190ba673a0ee329e671 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:49 p.m.