Triple
T1395508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mil Mi-24 |
E30655
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Mi-24K |
E30655
|
NE 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: Mi-24K | Statement: [Mil Mi-24, hasVariant, Mi-24K]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mi-24K Context triple: [Mil Mi-24, hasVariant, Mi-24K]
-
A.
Mi-24
chosen
The Mi-24 is a Soviet-designed attack helicopter and low-capacity troop transport, widely used for close air support and battlefield assault missions.
-
B.
Mi-17
The Mi-17 is a Russian-designed, medium-lift military transport helicopter widely used for troop transport, cargo missions, and search-and-rescue operations.
-
C.
Mi-8
The Mi-8 is a Soviet-designed twin-turbine transport helicopter widely used around the world for both military and civilian roles.
-
D.
Gazelle helicopter
The Gazelle helicopter is a light, fast, and highly maneuverable French-designed utility and reconnaissance helicopter widely used by military forces for training, liaison, and observation roles.
-
E.
Lynx helicopter
The Lynx helicopter is a British multi-role military helicopter renowned for its agility and service with both army and naval aviation units worldwide.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c37fd6e0819084d610ef041db3af |
completed | March 1, 2026, 10:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad0e657d3c8190962220e52e3e64c0 |
completed | March 8, 2026, 5:51 a.m. |
Created at: March 1, 2026, 7:59 p.m.