Triple

T28858020
Position Surface form Disambiguated ID Type / Status
Subject Bentley BR2 E728788 entity
Predicate usedOnAircraft P10706 FINISHED
Object Gloster Sparrowhawk
The Gloster Sparrowhawk was a British single-seat biplane fighter developed shortly after World War I and used primarily by the Imperial Japanese Navy in the 1920s.
E1842308 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: Gloster Sparrowhawk | Statement: [Bentley BR2, usedOnAircraft, Gloster Sparrowhawk]
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: Gloster Sparrowhawk
Triple: [Bentley BR2, usedOnAircraft, Gloster Sparrowhawk]
Generated description
The Gloster Sparrowhawk was a British single-seat biplane fighter developed shortly after World War I and used primarily by the Imperial Japanese Navy in the 1920s.

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_69f0319f4e5481909e4c439dbe8be940 completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f65a13c9b08190961c85e2c61c16b7 completed May 2, 2026, 8:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec2d421c8190b6d510de327f3a0f completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f07e3a54819090dc0d92cee92204 completed June 7, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a24f56a17a48190a309ea59a2ebf4d1 completed June 7, 2026, 4:36 a.m.
Created at: April 28, 2026, 6:46 a.m.