Triple

T38330479
Position Surface form Disambiguated ID Type / Status
Subject Harry DeWolf-class E1037807 entity
Predicate secondShip P75728 FINISHED
Object HMCS Margaret Brooke
HMCS Margaret Brooke is a Royal Canadian Navy Arctic and Offshore Patrol Ship named in honor of Canadian naval hero and nurse Margaret Brooke.
 E2269070 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 Margaret Brooke | Statement: [Harry DeWolf-class, secondShip, HMCS Margaret Brooke]
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 Margaret Brooke
Triple: [Harry DeWolf-class, secondShip, HMCS Margaret Brooke]
Generated description
HMCS Margaret Brooke is a Royal Canadian Navy Arctic and Offshore Patrol Ship named in honor of Canadian naval hero and nurse Margaret Brooke.

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_69f76e20d65c81909619ac0dd85c56f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc6b7444c81909dc7602bf6a989d0 completed May 7, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41c275625881908e1153d4064a86d9 completed June 29, 2026, 12:55 a.m.
NEDg Description generation batch_6a41c347ae908190ae32914fd32848f1 completed June 29, 2026, 12:58 a.m.
NED2 Entity disambiguation (via description) batch_6a41c3cd2f7081909cba8f277a165063 completed June 29, 2026, 1:01 a.m.
Created at: May 3, 2026, 4:30 p.m.