Triple
T22876419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thinking Machines Corporation |
E567336
|
entity |
| Predicate | usedProgrammingLanguage |
P1592
|
FINISHED |
| Object | CM Lisp |
—
|
NE NERFINISHED |
How this triple was built (3 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: CM Lisp | Statement: [Thinking Machines Corporation, usedProgrammingLanguage, CM Lisp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CM Lisp Context triple: [Thinking Machines Corporation, usedProgrammingLanguage, CM Lisp]
-
A.
CMU Common Lisp
CMU Common Lisp is a high-performance, open-source implementation of the Common Lisp programming language developed at Carnegie Mellon University, notable for its advanced compiler and optimization capabilities.
-
B.
CLISP
CLISP is a portable, open-source implementation of the Common Lisp programming language featuring an interpreter, compiler, and extensive standard library support.
-
C.
Maclisp
Maclisp is an early and influential dialect of the Lisp programming language developed at MIT, notable for shaping later Lisp systems and language designs.
-
D.
Common Lisp
Common Lisp is a powerful, multi-paradigm dialect of the Lisp programming language standardised in the 1980s, known for its rich macro system, dynamic typing, and suitability for large-scale, extensible software systems.
-
E.
Symbolics Common Lisp implementation
The Symbolics Common Lisp implementation is a specialized, high-performance version of the Common Lisp language designed for Symbolics Lisp machines, featuring advanced development tools and tight integration with the hardware and operating system.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CM Lisp Target entity description: CM Lisp is a parallel extension of the Common Lisp programming language designed for use on Thinking Machines Corporation’s Connection Machine supercomputers.
-
A.
CMU Common Lisp
CMU Common Lisp is a high-performance, open-source implementation of the Common Lisp programming language developed at Carnegie Mellon University, notable for its advanced compiler and optimization capabilities.
-
B.
CLISP
CLISP is a portable, open-source implementation of the Common Lisp programming language featuring an interpreter, compiler, and extensive standard library support.
-
C.
Maclisp
Maclisp is an early and influential dialect of the Lisp programming language developed at MIT, notable for shaping later Lisp systems and language designs.
-
D.
Common Lisp
Common Lisp is a powerful, multi-paradigm dialect of the Lisp programming language standardised in the 1980s, known for its rich macro system, dynamic typing, and suitability for large-scale, extensible software systems.
-
E.
Symbolics Common Lisp implementation
The Symbolics Common Lisp implementation is a specialized, high-performance version of the Common Lisp language designed for Symbolics Lisp machines, featuring advanced development tools and tight integration with the hardware and operating system.
- F. None of above. chosen
Provenance (2 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f58a7308190b710bdf013e2e114 |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.