Triple
T31582742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VT52 |
E805868
|
entity |
| Predicate | supportsInsertDeleteLine |
P207466
|
FINISHED |
| Object | model-dependent |
—
|
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: model-dependent | Statement: [VT52, supportsInsertDeleteLine, model-dependent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsInsertDeleteLine Context triple: [VT52, supportsInsertDeleteLine, model-dependent]
-
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.
lineReplaced
Indicates that one line has been substituted or superseded by another line, typically in a versioning, editing, or modification context.
-
C.
supportsBackspaceOverstrike
Indicates that an entity allows the use of backspace characters to overstrike and modify previously printed or displayed characters.
-
D.
interchangeWithLine
Indicates that one entity can be transferred or switched to another specific line, such as a route, track, or service line, at a given point.
-
E.
supportsBadLines
Indicates that one entity is capable of handling, accepting, or operating correctly even when provided with malformed, invalid, or otherwise “bad” lines of input or data.
- 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_69f348d3a86c8190a3e5e539a4dd125f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 10:24 p.m.