Triple
T21832322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MOS Technology VIC-II |
E539027
|
entity |
| Predicate | supportsBadLines |
P145473
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [MOS Technology VIC-II, supportsBadLines, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBadLines Context triple: [MOS Technology VIC-II, supportsBadLines, true]
-
A.
supportsLine
Indicates that one entity provides structural, functional, or conceptual backing or reinforcement to a particular line (such as a line of text, code, argument, or physical alignment).
-
B.
supportsFailure
Indicates that one entity provides assistance, resources, or backing to another entity specifically in situations of error, malfunction, or unsuccessful outcomes.
-
C.
supportsOneLiners
Indicates that one entity provides or enables concise, single-line expressions or statements for another entity.
-
D.
usesLineCharacteristic
Indicates that one entity employs or is based on a specific characteristic or property of a line.
-
E.
supportsBorders
Indicates that one entity endorses, maintains, or upholds the existence or enforcement of boundaries or borders associated with another entity.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7a4d2d0819088ded045caeab52d |
completed | April 28, 2026, 12:27 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
| PDg | Predicate description generation | batch_69e6c187bc548190b4ca13150f6bae38 |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 6:55 p.m.