Triple
T6626420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklands |
E149814
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Hawker |
E8218
|
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: Hawker | Statement: [Brooklands, associatedWith, Hawker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hawker Context triple: [Brooklands, associatedWith, Hawker]
-
A.
Hawker
Hawker is a surname of English origin borne by various notable individuals across fields such as aviation, politics, and the arts.
-
B.
Hawker Aircraft
chosen
Hawker Aircraft was a prominent British aircraft manufacturer best known for producing iconic military planes such as the Hawker Hurricane during the early to mid-20th century.
-
C.
Hawker Hart
The Hawker Hart was a British two-seat biplane light bomber of the interwar period, renowned for its high performance and extensive service with the Royal Air Force in the 1930s.
-
D.
Avro
Avro is a row-oriented, schema-based data serialization format commonly used in big data processing and storage systems.
-
E.
Avro
Avro was a British aircraft manufacturer best known for producing iconic military aircraft such as the Avro Lancaster bomber during the 20th century.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afa0feb0819099629c0fba590a05 |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e44d356c8190ad4f2a617c3de4af |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:58 p.m.