Triple
T26966684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BPP |
E679189
|
entity |
| Predicate | errorDirection |
P162013
|
FINISHED |
| Object | allows both false positives and false negatives |
—
|
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: allows both false positives and false negatives | Statement: [BPP, errorDirection, allows both false positives and false negatives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorDirection Context triple: [BPP, errorDirection, allows both false positives and false negatives]
-
A.
errorSide
Indicates the side, party, or component on which an error occurs or is attributed in a given context.
-
B.
offsetDirection
Indicates the relative direction in which one entity is displaced or shifted from another reference entity.
-
C.
errorTerm
Indicates the specific discrepancy or residual value that quantifies the difference between an observed outcome and its predicted or true value in a model or calculation.
-
D.
errorType
Indicates the specific category or kind of error associated with an event, action, or entity.
-
E.
errorPhase
Indicates the specific stage or phase in a process or workflow during which an error occurred.
- 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621c7d3e0819095b1f327637ae4f9 |
completed | May 2, 2026, 4:09 p.m. |
Created at: April 27, 2026, 6:36 a.m.