Triple
T35779827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 747-400F |
E1034405
|
entity |
| Predicate | typicalLowerHoldCargoVolume |
P17923
|
FINISHED |
| Object | approximately 32 LD-1 containers or pallets |
—
|
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: approximately 32 LD-1 containers or pallets | Statement: [Boeing 747-400F, typicalLowerHoldCargoVolume, approximately 32 LD-1 containers or pallets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLowerHoldCargoVolume Context triple: [Boeing 747-400F, typicalLowerHoldCargoVolume, approximately 32 LD-1 containers or pallets]
-
A.
cargoHoldVolume
chosen
Indicates the total internal volume available within a cargo hold for storing goods or materials.
-
B.
hasCargoHold
Indicates that something possesses a dedicated space or compartment for storing or transporting cargo.
-
C.
cargoHoldWidth
Indicates the width dimension of a cargo hold in a vehicle, vessel, or storage structure.
-
D.
cargoHoldHeight
Indicates the vertical interior dimension or clearance height of a cargo hold space.
-
E.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
- 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_69f76e14a1e081908eddd57bd6fdb3be |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.