Triple
T11958620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AdaCore |
E284613
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object |
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.
|
E956206
|
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: GNAT for Python | Statement: [AdaCore, product, GNAT for Python]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GNAT for Python Context triple: [AdaCore, product, GNAT for Python]
-
A.
gnat
GNAT is a free, open-source Ada compiler and toolchain that is part of the GNU Compiler Collection (GCC).
-
B.
GNATmake
GNATmake is the GNAT Ada compiler’s build tool that automatically manages multi-file project compilation and dependency tracking.
-
C.
AdaCore
AdaCore is a software company specializing in high-integrity, safety- and security-critical development tools and compilers for the Ada programming language.
-
D.
GNU Pascal
GNU Pascal is a free, open-source Pascal compiler that is part of the GNU project and designed to be compatible with various Pascal standards.
-
E.
Cython
Cython is a programming language and compiler that extends Python with static typing and direct C/C++ integration to generate fast, optimized extension modules.
- 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: GNAT for Python Triple: [AdaCore, product, GNAT for Python]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GNAT for Python Target entity description: 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.
-
A.
gnat
GNAT is a free, open-source Ada compiler and toolchain that is part of the GNU Compiler Collection (GCC).
-
B.
GNATmake
GNATmake is the GNAT Ada compiler’s build tool that automatically manages multi-file project compilation and dependency tracking.
-
C.
AdaCore
AdaCore is a software company specializing in high-integrity, safety- and security-critical development tools and compilers for the Ada programming language.
-
D.
GNU Pascal
GNU Pascal is a free, open-source Pascal compiler that is part of the GNU project and designed to be compatible with various Pascal standards.
-
E.
Cython
Cython is a programming language and compiler that extends Python with static typing and direct C/C++ integration to generate fast, optimized extension modules.
- 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_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_69f459210d1c8190953cd01da3d2ad04 |
completed | May 1, 2026, 7:41 a.m. |
| NEDg | Description generation | batch_69f4645ef63881909b46937f73d637a3 |
completed | May 1, 2026, 8:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f465be4db08190882898a17d077019 |
completed | May 1, 2026, 8:35 a.m. |
Created at: April 8, 2026, 9:45 p.m.