Triple
T15925699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markus Oberhumer |
E386199
|
entity |
| Predicate | softwareCreated |
P43636
|
FINISHED |
| Object | UPX |
E82617
|
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: UPX | Statement: [Markus Oberhumer, softwareCreated, UPX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UPX Context triple: [Markus Oberhumer, softwareCreated, UPX]
-
A.
UPX
chosen
UPX is an executable packer and compressor commonly used to reduce the size of binary programs.
-
B.
UPX
UPX is a dedicated airport rail link in the Greater Toronto Area that connects Union Station in downtown Toronto with Toronto Pearson International Airport.
-
C.
7zip
7zip is a high-compression open-source archive format commonly used for efficiently packaging and reducing the size of files.
-
D.
Engrampa archive manager
Engrampa archive manager is the MATE desktop environment’s file archiving tool used to create, view, and extract compressed archives in various formats.
-
E.
ustar
ustar is the standardized POSIX variant of the tar archive format, designed to ensure consistent file archiving and portability across Unix-like systems.
- 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15685b28c8190927b704fef14a159 |
completed | April 16, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3bd67f48190aee4f892206d9326 |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:52 a.m.