Triple
T2753948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tupolev Tu-20 / Tu-95 |
E61055
|
entity |
| Predicate | Tu-142Role |
P2860
|
FINISHED |
| Object | maritime patrol and anti-submarine warfare |
—
|
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: maritime patrol and anti-submarine warfare | Statement: [Tupolev Tu-20 / Tu-95, Tu-142Role, maritime patrol and anti-submarine warfare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Tu-142Role Context triple: [Tupolev Tu-20 / Tu-95, Tu-142Role, maritime patrol and anti-submarine warfare]
-
A.
basedAircraftRole
Indicates that an aircraft is regularly stationed at a particular location in a specified operational role or function.
-
B.
usesCarrierAircraft
Indicates that one entity employs or operates aircraft that are designed to be launched from and recovered by an aircraft carrier.
-
C.
fleetType
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
-
D.
primaryAircraftRole
chosen
Indicates the main operational function or mission type an aircraft is primarily designed or used to perform.
-
E.
aircraftTypesCarried
Indicates that one entity (typically a vessel, facility, or platform) carries or is capable of carrying specific types of aircraft as part of its operations or configuration.
- 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb7073d081909da84b21015972f2 |
completed | March 7, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69abd82d005c81908a1ac7a1313c6d88 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.