Triple
T6370835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LambdaProlog |
E143339
|
entity |
| Predicate | extends |
P1244
|
FINISHED |
| Object | Prolog |
E440678
|
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: Prolog | Statement: [LambdaProlog, extends, Prolog]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prolog Context triple: [LambdaProlog, extends, Prolog]
-
A.
Prolog
chosen
Prolog is a high-level logic programming language rooted in formal logic and widely used in artificial intelligence, natural language processing, and symbolic reasoning.
-
B.
LambdaProlog
LambdaProlog is a logic programming language that extends Prolog with higher-order features, polymorphism, and strong support for reasoning about formal systems and syntax with bindings.
-
C.
Franz Lisp
Franz Lisp is a dialect of the Lisp programming language developed in the late 1970s at the University of California, Berkeley, primarily for use in artificial intelligence research and symbolic computation.
-
D.
Lisp programming language
Lisp is a pioneering high-level programming language, especially influential in artificial intelligence research and known for its symbolic processing and distinctive parenthesized syntax.
-
E.
Chez Scheme
Chez Scheme is a high-performance, optimizing implementation of the Scheme programming language widely used for both research and production systems.
- 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_69c008d8c61081908bcaf61510d881ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c068277f6c81908e6a55e006f0c229 |
completed | March 22, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6386f361c819098dbe01b0cb07b06 |
completed | March 27, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:33 p.m.