Triple

T33100892
Position Surface form Disambiguated ID Type / Status
Subject Henry Redhead Yorke E847038 entity
Predicate notableWork P4 FINISHED
Object Letters from France
Letters from France is a political and travel commentary work by Henry Redhead Yorke, offering his observations and reflections on French society and revolutionary politics.
E2037081 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: Letters from France | Statement: [Henry Redhead Yorke, notableWork, Letters from France]
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: Letters from France
Triple: [Henry Redhead Yorke, notableWork, Letters from France]
Generated description
Letters from France is a political and travel commentary work by Henry Redhead Yorke, offering his observations and reflections on French society and revolutionary politics.

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_69f3495686508190b76bf20fa5e00bf7 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d6acf2a481909f90970921efe7ec completed May 3, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34f02ee8cc8190bff0844cc68cad58 completed June 19, 2026, 7:30 a.m.
NEDg Description generation batch_6a350b1c38a88190a4f51a96b37cc054 completed June 19, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_6a3510cb22ac8190a50e6709c5281bf6 completed June 19, 2026, 9:50 a.m.
Created at: May 1, 2026, 1:26 a.m.