Triple

T31832741
Position Surface form Disambiguated ID Type / Status
Subject Flintshire Militia E812581 entity
Predicate partOf P40 FINISHED
Object British Militia
The British Militia was a part-time, locally raised military force in Britain composed mainly of civilian soldiers organized for home defense and internal security, especially prominent from the 18th to 19th centuries.
 E1979802 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: British Militia | Statement: [Flintshire Militia, partOf, British Militia]
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: British Militia
Triple: [Flintshire Militia, partOf, British Militia]
Generated description
The British Militia was a part-time, locally raised military force in Britain composed mainly of civilian soldiers organized for home defense and internal security, especially prominent from the 18th to 19th centuries.

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_69f348ea7ffc8190a2ab43d80277cf59 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6afebd7ec8190ab696f363d84abf0 completed May 3, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e65a46ac081909b1842be063e0e12 completed June 14, 2026, 8:26 a.m.
NEDg Description generation batch_6a2e66d85dc481908d7a51e1b0747601 completed June 14, 2026, 8:31 a.m.
NED2 Entity disambiguation (via description) batch_6a2e678bedb48190b9f7728aa5606420 completed June 14, 2026, 8:34 a.m.
Created at: April 30, 2026, 11:47 p.m.