Triple
T27885602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reversi |
E705213
|
entity |
| Predicate | hasComputerPrograms |
P199762
|
FINISHED |
| Object | strong AI engines exist |
—
|
LITERAL 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: strong AI engines exist | Statement: [Reversi, hasComputerPrograms, strong AI engines exist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComputerPrograms Context triple: [Reversi, hasComputerPrograms, strong AI engines exist]
-
A.
hasProgrammingDomain
Indicates that an entity is associated with or specializes in a particular programming domain or area of software development.
-
B.
hasProgrammingFrom
Indicates that something derives its programming, configuration, or behavioral instructions from a specified source.
-
C.
hasLanguageOfProgramming
Indicates that an entity uses, is implemented in, or is otherwise associated with a particular programming language.
-
D.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
-
E.
hasProgrammingScope
Indicates that something (such as a role, task, or activity) involves or includes programming-related responsibilities or subject matter.
- F. None of above. chosen
Provenance (4 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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69ff56ef0a5c8190ae729d66a8cf7fc4 |
completed | May 9, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ff539859c481909ec56310da418688 |
completed | May 9, 2026, 3:32 p.m. |
| PDg | Predicate description generation | batch_69ff56edc4d081908f1d263e05cbd512 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 27, 2026, 6:32 p.m.