Triple

T27733837
Position Surface form Disambiguated ID Type / Status
Subject System.Text E697487 entity
Predicate containsType P16808 FINISHED
Object System.Text.EncoderExceptionFallback
System.Text.EncoderExceptionFallback is a .NET text encoding fallback strategy that throws an exception whenever a character cannot be encoded instead of silently substituting a replacement.
 E1789148 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: System.Text.EncoderExceptionFallback | Statement: [System.Text, containsType, System.Text.EncoderExceptionFallback]
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: System.Text.EncoderExceptionFallback
Triple: [System.Text, containsType, System.Text.EncoderExceptionFallback]
Generated description
System.Text.EncoderExceptionFallback is a .NET text encoding fallback strategy that throws an exception whenever a character cannot be encoded instead of silently substituting a replacement.

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_69ef590c3e288190ad54d2465af8ca4e completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f6369fa1d88190ac40370ec4fa185e completed May 2, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12eca90eb88190819910f3030f56e3 completed May 24, 2026, 12:18 p.m.
NEDg Description generation batch_6a12ed678580819082d28135e3fcb818 completed May 24, 2026, 12:21 p.m.
NED2 Entity disambiguation (via description) batch_6a12eef54e2c8190b9e8d589f036b066 completed May 24, 2026, 12:28 p.m.
Created at: April 27, 2026, 3:12 p.m.