Triple
T1053364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing AH-64 Apache |
E22747
|
entity |
| Predicate | crewArrangement |
P16826
|
FINISHED |
| Object | tandem |
—
|
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 | Statement: [Boeing AH-64 Apache, crewArrangement, tandem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewArrangement Context triple: [Boeing AH-64 Apache, crewArrangement, tandem]
-
A.
crewType
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
-
B.
crew
Indicates that one entity serves as the group of people who operate, staff, or work on another entity (such as a vehicle, vessel, or production).
-
C.
arrangement
Indicates a relationship where entities are organized, ordered, or positioned in a particular configuration or sequence relative to one another.
-
D.
seatingConfiguration
chosen
Indicates how seats are arranged or organized relative to each other in a given context.
-
E.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b644088190a1f0f00f97941298 |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b731e25c8190b5ea8466648c2c9a |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.