Triple

T29870985
Position Surface form Disambiguated ID Type / Status
Subject POWER4 E758592 entity
Predicate operatingSystems P1593 FINISHED
Object Linux on Power
Linux on Power is a port of the Linux operating system optimized to run on IBM's Power Architecture processors, providing a scalable, high-performance platform for enterprise and technical computing.
E204899 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: Linux on Power | Statement: [POWER4, operatingSystems, Linux on Power]
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: Linux on Power
Triple: [POWER4, operatingSystems, Linux on Power]
Generated description
Linux on Power is a port of the Linux operating system optimized to run on IBM's Power Architecture processors, providing a scalable, high-performance platform for enterprise and technical computing.

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_69f2245d0d7081909e37ee328542bcd7 completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69ff0e08fe008190b09fa58faed91072 completed May 9, 2026, 10:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a26f1cf642881909362077f3082b1dd completed June 8, 2026, 4:46 p.m.
NEDg Description generation batch_6a26f2a076d4819086a7a4bf85946196 completed June 8, 2026, 4:49 p.m.
NED2 Entity disambiguation (via description) batch_6a26f34f9b488190b90e3e36cf7174dc completed June 8, 2026, 4:52 p.m.
Created at: April 29, 2026, 5:53 p.m.