Triple
T3210223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sukhoi Su-27 |
E67260
|
entity |
| Predicate | NATOReportingName |
P6062
|
FINISHED |
| Object |
Flanker
Flanker is the NATO reporting name for the Sukhoi Su-27, a highly maneuverable Soviet-designed air superiority fighter aircraft.
|
E337823
|
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: Flanker | Statement: [Sukhoi Su-27, NATOReportingName, Flanker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flanker Context triple: [Sukhoi Su-27, NATOReportingName, Flanker]
-
A.
Matfield
Matfield is a small rural village in Kent, England, known for its traditional village green and historic buildings.
-
B.
Crennel
Crennel is the surname of Romeo Crennel, an American football coach best known for his roles as an NFL head coach and defensive coordinator.
-
C.
Victor Matfield
Victor Matfield is a renowned South African rugby union lock, widely regarded as one of the greatest line-out specialists and key figures in the Springboks’ World Cup–winning era.
-
D.
Bryan Habana
Bryan Habana is a legendary South African rugby union wing renowned for his exceptional speed and prolific try-scoring for the Springboks.
-
E.
Bronk
Bronk is a surname most notably associated with Detlev W. Bronk, an influential American scientist and educator who helped shape modern biophysics and higher education policy.
- 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: Flanker Triple: [Sukhoi Su-27, NATOReportingName, Flanker]
Generated description
Flanker is the NATO reporting name for the Sukhoi Su-27, a highly maneuverable Soviet-designed air superiority fighter aircraft.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Flanker Target entity description: Flanker is the NATO reporting name for the Sukhoi Su-27, a highly maneuverable Soviet-designed air superiority fighter aircraft.
-
A.
Matfield
Matfield is a small rural village in Kent, England, known for its traditional village green and historic buildings.
-
B.
Crennel
Crennel is the surname of Romeo Crennel, an American football coach best known for his roles as an NFL head coach and defensive coordinator.
-
C.
Victor Matfield
Victor Matfield is a renowned South African rugby union lock, widely regarded as one of the greatest line-out specialists and key figures in the Springboks’ World Cup–winning era.
-
D.
Bryan Habana
Bryan Habana is a legendary South African rugby union wing renowned for his exceptional speed and prolific try-scoring for the Springboks.
-
E.
Bronk
Bronk is a surname most notably associated with Detlev W. Bronk, an influential American scientist and educator who helped shape modern biophysics and higher education policy.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaab886c48190b72e36d0ac855ffe |
completed | March 8, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2622d4e988190a8a98a0bc9353e3f |
completed | March 12, 2026, 6:50 a.m. |
| NEDg | Description generation | batch_69b264c446088190a1651e108279c7ba |
completed | March 12, 2026, 7:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b265ef74d081908fe4dd4998dbf240 |
completed | March 12, 2026, 7:06 a.m. |
Created at: March 8, 2026, 3:07 p.m.