Triple

T27615839
Position Surface form Disambiguated ID Type / Status
Subject .NET Base Class Library E700434 entity
Predicate containsNamespace P79649 FINISHED
Object System.Globalization
System.Globalization is a .NET namespace that provides classes and APIs for culture-aware operations such as formatting dates and numbers, handling calendars, and managing internationalization and localization.
E1782147 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.Globalization | Statement: [.NET Base Class Library, containsNamespace, System.Globalization]
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.Globalization
Triple: [.NET Base Class Library, containsNamespace, System.Globalization]
Generated description
System.Globalization is a .NET namespace that provides classes and APIs for culture-aware operations such as formatting dates and numbers, handling calendars, and managing internationalization and localization.

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_69ef6a4f1d9c8190b0705acda054368d completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69fd374dcc288190a1f2ec5d02802fd7 completed May 8, 2026, 1:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0efa9448190a53a6f8ed0c4d3af completed May 24, 2026, 10:20 a.m.
NEDg Description generation batch_6a12d4c2e97c81908ae5048a0afd4bc7 completed May 24, 2026, 10:36 a.m.
NED2 Entity disambiguation (via description) batch_6a12d52ae1ac8190a4ff238fc17fbab2 completed May 24, 2026, 10:38 a.m.
Created at: April 27, 2026, 2:12 p.m.