Triple

T26243985
Position Surface form Disambiguated ID Type / Status
Subject A2 operating system E656391 entity
Predicate programmingLanguage P1592 FINISHED
Object Active Oberon
Active Oberon is an object-oriented, concurrent programming language in the Oberon family, designed to support active objects and systems programming, particularly for the A2 operating system.
E1713757 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: Active Oberon | Statement: [A2 operating system, programmingLanguage, Active Oberon]
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: Active Oberon
Triple: [A2 operating system, programmingLanguage, Active Oberon]
Generated description
Active Oberon is an object-oriented, concurrent programming language in the Oberon family, designed to support active objects and systems programming, particularly for the A2 operating system.

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_69ee5b4c59a881909d9ee4fd013fffd5 completed April 26, 2026, 6:37 p.m.
NER Named-entity recognition batch_69f60dc4aa808190ba3b5682944a7fb8 completed May 2, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11859fed908190964838b467e91dc7 completed May 23, 2026, 10:46 a.m.
NEDg Description generation batch_6a11863dfad48190903b8defdb1f64f6 completed May 23, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a1186d5ad5c81908645150955c109dc completed May 23, 2026, 10:52 a.m.
Created at: April 26, 2026, 9:04 p.m.