Triple
T2753923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tupolev Tu-20 / Tu-95 |
E61055
|
entity |
| Predicate | NATOReportingName |
P6062
|
FINISHED |
| Object |
Bear
"Bear" is the NATO reporting name for the Tupolev Tu-95, a long-range, turboprop-powered strategic bomber and maritime patrol aircraft developed by the Soviet Union.
|
E310809
|
NE FINISHED |
How this triple was built (4 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: Bear | Statement: [Tupolev Tu-20 / Tu-95, NATOReportingName, Bear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bear Context triple: [Tupolev Tu-20 / Tu-95, NATOReportingName, Bear]
-
A.
bear
A bear is a large, typically omnivorous mammal known for its powerful build, thick fur, and presence in diverse habitats across the Northern Hemisphere and parts of the Southern Hemisphere.
-
B.
Badger
Badger is a fictional character appearing in the work "The Return of Ulysses."
-
C.
Badger
Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
-
D.
Badger
Badger is the NATO reporting name for the Soviet-era Tupolev Tu-16, a twin-engine jet strategic bomber widely used during the Cold War.
-
E.
Wolf
Wolf is a song by American singer Miguel from his album "War & Leisure."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bear Triple: [Tupolev Tu-20 / Tu-95, NATOReportingName, Bear]
Generated description
"Bear" is the NATO reporting name for the Tupolev Tu-95, a long-range, turboprop-powered strategic bomber and maritime patrol aircraft developed by the Soviet Union.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bear Target entity description: "Bear" is the NATO reporting name for the Tupolev Tu-95, a long-range, turboprop-powered strategic bomber and maritime patrol aircraft developed by the Soviet Union.
-
A.
bear
A bear is a large, typically omnivorous mammal known for its powerful build, thick fur, and presence in diverse habitats across the Northern Hemisphere and parts of the Southern Hemisphere.
-
B.
Badger
Badger is a fictional character appearing in the work "The Return of Ulysses."
-
C.
Badger
Badger is a wise, kind, and somewhat reclusive character from Kenneth Grahame’s "The Wind in the Willows," known for offering guidance and shelter to his woodland friends.
-
D.
Badger
Badger is the NATO reporting name for the Soviet-era Tupolev Tu-16, a twin-engine jet strategic bomber widely used during the Cold War.
-
E.
Wolf
Wolf is a song by American singer Miguel from his album "War & Leisure."
- F. None of above. chosen
Provenance (5 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. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055c4e58c8190809cc77161754246 |
completed | March 10, 2026, 5:32 p.m. |
| NEDg | Description generation | batch_69b064159d208190a66e465c86aa0d2a |
completed | March 10, 2026, 6:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b064a3b41481909214a09eae0b092b |
completed | March 10, 2026, 6:36 p.m. |
Created at: March 6, 2026, 9:56 p.m.