Triple

T26247778
Position Surface form Disambiguated ID Type / Status
Subject Maurice Suckling E656496 entity
Predicate shipServedOn P12804 FINISHED
Object HMS Nassau
HMS Nassau was a Royal Navy warship that served in the 18th century, notably as one of the early commands of naval officer Maurice Suckling, the uncle and mentor of Admiral Horatio Nelson.
E1801070 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 Nassau | Statement: [Maurice Suckling, shipServedOn, HMS Nassau]
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 Nassau
Triple: [Maurice Suckling, shipServedOn, HMS Nassau]
Generated description
HMS Nassau was a Royal Navy warship that served in the 18th century, notably as one of the early commands of naval officer Maurice Suckling, the uncle and mentor of Admiral Horatio Nelson.

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_69ee5b4c59a881909d9ee4fd013fffd5 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60dc7d2a081908645d06c02dc3e02 completed May 2, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b8633b008190a102b99892c11876 completed May 26, 2026, 3:12 p.m.
NEDg Description generation batch_6a15bd19b4908190942663430bf54817 completed May 26, 2026, 3:32 p.m.
NED2 Entity disambiguation (via description) batch_6a15bfdf6e7481909276897a678b012b completed May 26, 2026, 3:44 p.m.
Created at: April 26, 2026, 9:06 p.m.