Triple

T23979560
Position Surface form Disambiguated ID Type / Status
Subject North Pacific Force E604467 entity
Predicate notableShip P3345 FINISHED
Object HMCS Prince Henry
HMCS Prince Henry was a Royal Canadian Navy armed merchant cruiser and later landing ship that served notably in the Pacific and Atlantic during the Second World War.
E1619511 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: HMCS Prince Henry | Statement: [North Pacific Force, notableShip, HMCS Prince Henry]
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: HMCS Prince Henry
Triple: [North Pacific Force, notableShip, HMCS Prince Henry]
Generated description
HMCS Prince Henry was a Royal Canadian Navy armed merchant cruiser and later landing ship that served notably in the Pacific and Atlantic during the Second World War.

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_69e29543f40c819087700b7a272afb60 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d2bc79688190bc98a2d57b91f5a3 completed April 29, 2026, 9:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0facfbebec81909f2bbddeffbff6ea completed May 22, 2026, 1:10 a.m.
NEDg Description generation batch_6a0fad5e3ff0819080250111feb37ec2 completed May 22, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_6a0fadf7bbd08190aa99cd9d0e53afa1 completed May 22, 2026, 1:14 a.m.
Created at: April 17, 2026, 9:27 p.m.