Triple
T12516294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bzip2 |
E299198
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
pbzip2
pbzip2 is a parallel implementation of the bzip2 compression algorithm designed to take advantage of multi-core and multi-processor systems for faster file compression and decompression.
|
E986437
|
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: pbzip2 | Statement: [bzip2, influenced, pbzip2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: pbzip2 Context triple: [bzip2, influenced, pbzip2]
-
A.
bzip2
bzip2 is a free and open-source data compression program known for its high compression ratios using the Burrows–Wheeler algorithm.
-
B.
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.
-
C.
7zip
7zip is a high-compression open-source archive format commonly used for efficiently packaging and reducing the size of files.
-
D.
gzip
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.
-
E.
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.
- 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: pbzip2 Triple: [bzip2, influenced, pbzip2]
Generated description
pbzip2 is a parallel implementation of the bzip2 compression algorithm designed to take advantage of multi-core and multi-processor systems for faster file compression and decompression.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: pbzip2 Target entity description: pbzip2 is a parallel implementation of the bzip2 compression algorithm designed to take advantage of multi-core and multi-processor systems for faster file compression and decompression.
-
A.
bzip2
bzip2 is a free and open-source data compression program known for its high compression ratios using the Burrows–Wheeler algorithm.
-
B.
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.
-
C.
7zip
7zip is a high-compression open-source archive format commonly used for efficiently packaging and reducing the size of files.
-
D.
gzip
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.
-
E.
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.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541f80148190976d1d912fe155d0 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bbd58b88190baeb99380babf64f |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce257348190b01179773992d414 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64db823bc819098152a96db960b10 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 8, 2026, 9:57 p.m.