Triple
T11422045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motorola 68851 |
E270645
|
entity |
| Predicate | hasTranslationTable |
P99226
|
FINISHED |
| Object | root pointer register |
—
|
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: root pointer register | Statement: [Motorola 68851, hasTranslationTable, root pointer register]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTranslationTable Context triple: [Motorola 68851, hasTranslationTable, root pointer register]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasTranslationBase
Indicates that one entity serves as the original source or base text from which the other entity is translated.
-
C.
hasTransliterationRule
Indicates that there exists a specific rule or mapping that defines how text in one script or writing system is systematically converted into another.
-
D.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
-
E.
hasTranslationNote
Indicates that there is an explanatory note about how something has been translated, such as clarifying wording choices, alternatives, or translation issues.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801b357e88190ace56d36a945688f |
completed | April 9, 2026, 7:44 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
| PDg | Predicate description generation | batch_69d80010712c819089ea2e31e664abe1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:34 p.m.