Triple
T5008663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airco DH.9 |
E112559
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Airco |
E111131
|
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: Airco | Statement: [Airco DH.9, manufacturer, Airco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Airco Context triple: [Airco DH.9, manufacturer, Airco]
-
A.
Airco
chosen
Airco was a British aircraft manufacturer best known for producing military aircraft during World War I, including the successful DH series of biplanes.
-
B.
Vickers
Vickers is a surname of English origin borne by various notable individuals across fields such as entertainment, industry, and the military.
-
C.
Vickers-Armstrongs
Vickers-Armstrongs was a major British engineering and armaments company best known for producing military aircraft, ships, and tanks during the first half of the 20th century.
-
D.
Bristol Siddeley
Bristol Siddeley was a British aero engine manufacturer known for developing innovative jet and turbofan engines before its merger into Rolls-Royce.
-
E.
Avro
Avro is a row-oriented, schema-based data serialization format commonly used in big data processing and storage systems.
- 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd72eb05f881908d7dc3d7cd07b2ae |
completed | March 20, 2026, 4:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9266314881909dfb710c5b5c8f65 |
completed | March 21, 2026, 12:43 p.m. |
Created at: March 20, 2026, 1:35 p.m.