Triple

T25509979
Position Surface form Disambiguated ID Type / Status
Subject HMS Sophie E639347 entity
Predicate basedOn P98 FINISHED
Object HMS Speedy
HMS Speedy was a small, fast British Royal Navy brig-sloop of the late 18th and early 19th centuries, best known for her daring exploits under the command of Thomas Cochrane during the Napoleonic Wars.
E1706612 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: HMS Speedy | Statement: [HMS Sophie, basedOn, HMS Speedy]
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: HMS Speedy
Triple: [HMS Sophie, basedOn, HMS Speedy]
Generated description
HMS Speedy was a small, fast British Royal Navy brig-sloop of the late 18th and early 19th centuries, best known for her daring exploits under the command of Thomas Cochrane during the Napoleonic Wars.

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_69e75dbd09308190b6b5f0afdc12ec6d completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f809726081908ae4122cd4e581c1 completed May 2, 2026, 1:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111ae7e6008190939e7d418b390414 completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111c7f25788190ab64d5bd35a691c3 completed May 23, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a111d2b601881909f79329b949194e5 completed May 23, 2026, 3:21 a.m.
Created at: April 21, 2026, 2:48 p.m.