Triple

T38575982
Position Surface form Disambiguated ID Type / Status
Subject HMS Gurkha (F63) E929401 entity
Predicate namedAs P39771 FINISHED
Object HMS Gurkha
HMS Gurkha was a Royal Navy Tribal-class destroyer that served during the early years of World War II before being sunk in 1940.
E2286284 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 Gurkha | Statement: [HMS Gurkha (F63), namedAs, HMS Gurkha]
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 Gurkha
Triple: [HMS Gurkha (F63), namedAs, HMS Gurkha]
Generated description
HMS Gurkha was a Royal Navy Tribal-class destroyer that served during the early years of World War II before being sunk in 1940.

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_69f76ebd2248819083978362d81fa35e completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd9203be8819082090188d067c6a2 completed May 7, 2026, 6:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a469fc3fd80819086a3f5b954ad612a completed July 2, 2026, 5:28 p.m.
NEDg Description generation batch_6a46a1db0c2881908f963d15b2402a50 completed July 2, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_6a46a20843948190b241b220bf8a6ea5 completed July 2, 2026, 5:38 p.m.
Created at: May 3, 2026, 4:32 p.m.