Triple

T38453476
Position Surface form Disambiguated ID Type / Status
Subject Margaret Calvert E912240 entity
Predicate notableWork P4 FINISHED
Object New Rail Alphabet typeface
New Rail Alphabet typeface is a modernized revival of the classic British Rail signage lettering, designed by Margaret Calvert and Henrik Kubel for contemporary transport and information systems.
E2269333 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: New Rail Alphabet typeface | Statement: [Margaret Calvert, notableWork, New Rail Alphabet typeface]
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: New Rail Alphabet typeface
Triple: [Margaret Calvert, notableWork, New Rail Alphabet typeface]
Generated description
New Rail Alphabet typeface is a modernized revival of the classic British Rail signage lettering, designed by Margaret Calvert and Henrik Kubel for contemporary transport and information systems.

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_69f76e84e2dc81908badf05b3aafa9ea completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fccdffc43c8190a4c24316e19d071b completed May 7, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41c2a62c3c8190b13ec55f9433206d completed June 29, 2026, 12:56 a.m.
NEDg Description generation batch_6a41c33375888190ae12623e40f24041 completed June 29, 2026, 12:58 a.m.
NED2 Entity disambiguation (via description) batch_6a41c3b0ec6c8190becf6b8f5287b129 completed June 29, 2026, 1 a.m.
Created at: May 3, 2026, 4:31 p.m.