Triple
T11958664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GNATmake |
E284614
|
entity |
| Predicate | uses |
P98
|
FINISHED |
| Object | GNAT binder |
E956199
|
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: GNAT binder | Statement: [GNATmake, uses, GNAT binder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GNAT binder Context triple: [GNATmake, uses, GNAT binder]
-
A.
GNAT binder
chosen
GNAT binder is a tool in the GNAT Ada compilation system that analyzes and links Ada units, determining their elaboration order and generating the final executable.
-
B.
GNATmake
GNATmake is the GNAT Ada compiler’s build tool that automatically manages multi-file project compilation and dependency tracking.
-
C.
gnat
GNAT is a free, open-source Ada compiler and toolchain that is part of the GNU Compiler Collection (GCC).
-
D.
GNAT for Python
GNAT for Python is an AdaCore toolchain that enables writing and integrating Ada code within Python applications, combining Ada’s safety and reliability with Python’s flexibility.
-
E.
GNATtest
GNATtest is an AdaCore testing tool designed to automate the generation and execution of unit tests for Ada software.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903681a00819098c2b5260e2ef834 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f471d625c88190baed4ea08853988a |
completed | May 1, 2026, 9:26 a.m. |
Created at: April 8, 2026, 9:45 p.m.