Triple
T8414427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GNU userland |
E198698
|
entity |
| Predicate | includesComponent |
P1393
|
FINISHED |
| Object | GNU Gzip |
E299197
|
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: GNU Gzip | Statement: [GNU userland, includesComponent, GNU Gzip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GNU Gzip Context triple: [GNU userland, includesComponent, GNU Gzip]
-
A.
gzip
chosen
gzip is a widely used GNU file compression utility that reduces file size using the DEFLATE algorithm, commonly producing .gz archives on Unix-like systems.
-
B.
bzip2
bzip2 is a free and open-source data compression program known for its high compression ratios using the Burrows–Wheeler algorithm.
-
C.
GNU Tar
GNU Tar is a widely used free software utility for creating, maintaining, modifying, and extracting files from archive files, especially on Unix-like systems.
-
D.
lzip
lzip is a lossless data compression program and file format known for its high compression ratios, data integrity features, and use in software distribution archives.
-
E.
Zip2
Zip2 was an early online city guide and business directory software company from the late 1990s that provided web-based publishing tools for newspapers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e328cc8190b3b038005d0bb66f |
completed | March 31, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce032a25ec819094c6346eb2a7f973 |
completed | April 2, 2026, 5:48 a.m. |
Created at: March 30, 2026, 6:06 p.m.