Triple
T14568663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Britten-Norman Defender |
E341854
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Britten-Norman |
E341854
|
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: Britten-Norman | Statement: [Britten-Norman Defender, manufacturer, Britten-Norman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Britten-Norman Context triple: [Britten-Norman Defender, manufacturer, Britten-Norman]
-
A.
Britten-Norman Defender
chosen
The Britten-Norman Defender is a British twin-engine light utility and surveillance aircraft widely used for military, police, and border patrol operations.
-
B.
Avro
Avro is a row-oriented, schema-based data serialization format commonly used in big data processing and storage systems.
-
C.
Avro
Avro was a British aircraft manufacturer best known for producing iconic military aircraft such as the Avro Lancaster bomber during the 20th century.
-
D.
Folland Aircraft
Folland Aircraft was a British aircraft manufacturer best known for producing light fighter and trainer aircraft in the post-World War II era.
-
E.
Beechcraft
Beechcraft is an American aircraft manufacturer known for producing a wide range of civil and military airplanes, including popular training, business, and utility aircraft.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb38d89fc819086709fd3607b835f |
completed | April 14, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ac858108190b7c90130f18b0ddb |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:23 a.m.