Triple
T8609929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sabayon Linux |
E203891
|
entity |
| Predicate | previousName |
P65
|
FINISHED |
| Object |
RR64 Linux
RR64 Linux was the original name of the Sabayon Linux distribution, a Gentoo-based, user-friendly Linux operating system.
|
E745829
|
NE FINISHED |
How this triple was built (4 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: RR64 Linux | Statement: [Sabayon Linux, previousName, RR64 Linux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: RR64 Linux Context triple: [Sabayon Linux, previousName, RR64 Linux]
-
A.
R68
The R68 is a class of New York City Subway cars built in the 1980s for the B Division, known for their stainless-steel bodies and use on various lettered lines.
-
B.
BB-64
BB-64 is the hull number of USS Wisconsin, an Iowa-class battleship that served in the U.S. Navy during World War II, the Korean War, and the Gulf War.
-
C.
International Rice 64
International Rice 64 is a high-yielding, widely cultivated rice variety developed by the International Rice Research Institute and known for its significant impact on rice production in Asia.
-
D.
R4
R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
-
E.
R68A
R68A is a class of New York City Subway cars built in the late 1980s for B Division services, known for their stainless-steel bodies and use on lines such as the B and D.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: RR64 Linux Triple: [Sabayon Linux, previousName, RR64 Linux]
Generated description
RR64 Linux was the original name of the Sabayon Linux distribution, a Gentoo-based, user-friendly Linux operating system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: RR64 Linux Target entity description: RR64 Linux was the original name of the Sabayon Linux distribution, a Gentoo-based, user-friendly Linux operating system.
-
A.
R68
The R68 is a class of New York City Subway cars built in the 1980s for the B Division, known for their stainless-steel bodies and use on various lettered lines.
-
B.
BB-64
BB-64 is the hull number of USS Wisconsin, an Iowa-class battleship that served in the U.S. Navy during World War II, the Korean War, and the Gulf War.
-
C.
International Rice 64
International Rice 64 is a high-yielding, widely cultivated rice variety developed by the International Rice Research Institute and known for its significant impact on rice production in Asia.
-
D.
R4
R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
-
E.
R68A
R68A is a class of New York City Subway cars built in the late 1980s for B Division services, known for their stainless-steel bodies and use on lines such as the B and D.
- F. None of above. chosen
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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46ee96ac8190809817c403da2889 |
completed | March 31, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea90dd93081908140ac0ce23be820 |
completed | April 2, 2026, 5:36 p.m. |
| NEDg | Description generation | batch_69ceaa2c34308190a3bc7717012fea9d |
completed | April 2, 2026, 5:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ceaae76d188190932826c9fd9f7f5f |
completed | April 2, 2026, 5:44 p.m. |
Created at: March 30, 2026, 6:25 p.m.