Triple
T12516746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | diff3 |
E299207
|
entity |
| Predicate | documentation |
P4310
|
FINISHED |
| Object | GNU Diffutils manual |
E61966
|
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 Diffutils manual | Statement: [diff3, documentation, GNU Diffutils manual]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GNU Diffutils manual Context triple: [diff3, documentation, GNU Diffutils manual]
-
A.
GNU Diffutils
chosen
GNU Diffutils is a collection of GNU utilities for comparing files and directories, most notably providing the standard `diff` and `cmp` tools used on Unix-like systems.
-
B.
diff3
diff3 is a GNU Diffutils command-line program that compares and merges three versions of a file, commonly used for resolving merge conflicts.
-
C.
Ndiff
Ndiff is a component of the Nmap security scanner suite used to compare and analyze differences between network scan results.
-
D.
Magit
Magit is a powerful, interactive Git interface for the Emacs text editor that streamlines version control operations through a rich, keyboard-driven UI.
-
E.
"Unix Text Processing"
"Unix Text Processing" is a classic technical book that teaches practical techniques for manipulating and formatting text on Unix systems using tools like sed, awk, and troff.
- 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_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_69f6718cd6288190ad080f469f334caf |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.