Triple
T4275236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ripgrep |
E97033
|
entity |
| Predicate | comparedTo |
P278
|
FINISHED |
| Object | grep |
E61967
|
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: grep | Statement: [ripgrep, comparedTo, grep]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: grep Context triple: [ripgrep, comparedTo, grep]
-
A.
GNU Grep
chosen
GNU Grep is the GNU Project’s free, open-source implementation of the grep command-line utility used for fast text searching and pattern matching in files.
-
B.
egrep
egrep is a variant of the grep command-line utility that searches text using extended regular expressions for more powerful pattern matching.
-
C.
ripgrep
ripgrep is a fast, command-line search tool written in Rust that recursively searches directories using regular expressions and is widely used as a modern alternative to grep.
-
D.
GNU Findutils
GNU Findutils is a collection of essential GNU utilities, including the widely used `find`, `locate`, `updatedb`, and `xargs` tools, for searching and managing files on Unix-like systems.
-
E.
Regular Expression Search Algorithm
Regular Expression Search Algorithm is a pattern-matching method for efficiently finding text strings that match specified regular expressions, originally developed and formalized by computer scientist Ken Thompson.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501c35688190a7d15d904f15f968 |
completed | March 12, 2026, 11:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7b0b2ec819090ccf042917ae207 |
completed | March 14, 2026, 7:32 p.m. |
Created at: March 12, 2026, 11:07 p.m.