Triple

T33110850
Position Surface form Disambiguated ID Type / Status
Subject HMS Macedonia E847326 entity
Predicate partOf P40 FINISHED
Object 10th Cruiser Squadron
The 10th Cruiser Squadron was a Royal Navy formation of cruisers that operated primarily during World War I, notably conducting blockade and patrol duties in the North Atlantic.
E2039063 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: 10th Cruiser Squadron | Statement: [HMS Macedonia, partOf, 10th Cruiser Squadron]
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: 10th Cruiser Squadron
Triple: [HMS Macedonia, partOf, 10th Cruiser Squadron]
Generated description
The 10th Cruiser Squadron was a Royal Navy formation of cruisers that operated primarily during World War I, notably conducting blockade and patrol duties in the North Atlantic.

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_69f3495751a081909850af5843da40dc completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d6ea28548190afd18b171ae9532a completed May 3, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35161010f481909de0ac9e70c56782 completed June 19, 2026, 10:12 a.m.
NEDg Description generation batch_6a352052c3e081908dc2108569cfd408 completed June 19, 2026, 10:56 a.m.
NED2 Entity disambiguation (via description) batch_6a3520e458348190b6fb9438286a1d98 completed June 19, 2026, 10:58 a.m.
Created at: May 1, 2026, 1:27 a.m.