Triple

T28872069
Position Surface form Disambiguated ID Type / Status
Subject DICOM Transfer Syntax E732166 entity
Predicate hasExample P1259 FINISHED
Object Implicit VR Little Endian
Implicit VR Little Endian is a DICOM transfer syntax that encodes data elements without explicit value representations using little-endian byte ordering.
 E1837181 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: Implicit VR Little Endian | Statement: [DICOM Transfer Syntax, hasExample, Implicit VR Little Endian]
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: Implicit VR Little Endian
Triple: [DICOM Transfer Syntax, hasExample, Implicit VR Little Endian]
Generated description
Implicit VR Little Endian is a DICOM transfer syntax that encodes data elements without explicit value representations using little-endian byte ordering.

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_69f05b06807c81909b4bbd4c20403a2b completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69f65a47793481908efd891e27e541bf completed May 2, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24bbca11bc8190a5ca086b292bc308 completed June 7, 2026, 12:31 a.m.
NEDg Description generation batch_6a24c6cd18dc8190b5dd81a7443810ee completed June 7, 2026, 1:18 a.m.
NED2 Entity disambiguation (via description) batch_6a24c7444a28819093301b041d54b916 completed June 7, 2026, 1:20 a.m.
Created at: April 28, 2026, 7:33 a.m.