Triple

T24785542
Position Surface form Disambiguated ID Type / Status
Subject Rivers of London E620106 entity
Predicate coverArtist P184 FINISHED
Object Stephen Walter
Stephen Walter is a British artist and cartographer known for his intricately detailed, hand-drawn maps that blend geography with cultural and psychological landscapes.
 E1653713 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: Stephen Walter | Statement: [Rivers of London, coverArtist, Stephen Walter]
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: Stephen Walter
Triple: [Rivers of London, coverArtist, Stephen Walter]
Generated description
Stephen Walter is a British artist and cartographer known for his intricately detailed, hand-drawn maps that blend geography with cultural and psychological landscapes.

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_69e2fabdbe8c8190adbb9434b8636cad completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f410fe3b848190ae296a29f742ee30 completed May 1, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a101c25db188190a2c6b998d5d813bd completed May 22, 2026, 9:04 a.m.
NEDg Description generation batch_6a1028c1e21c8190a948d84f7e1d3a38 completed May 22, 2026, 9:58 a.m.
NED2 Entity disambiguation (via description) batch_6a102983964c8190b41cd36b87f8ad0a completed May 22, 2026, 10:01 a.m.
Created at: April 18, 2026, 4:45 a.m.