Triple
T34416002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Negation |
E883403
|
entity |
| Predicate | hasSemanticEffect |
P28757
|
FINISHED |
| Object | reverses proposition polarity |
—
|
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: reverses proposition polarity | Statement: [Negation, hasSemanticEffect, reverses proposition polarity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSemanticEffect Context triple: [Negation, hasSemanticEffect, reverses proposition polarity]
-
A.
hasDirectEffect
Indicates that one entity produces an immediate and unmediated impact or change on another entity.
-
B.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
C.
hasIntendedEffect
Indicates that one entity is expected or designed to produce a particular effect or outcome on another entity or context.
-
D.
hasSemantics
chosen
Indicates that one entity carries or encodes the meaning, interpretation, or semantic content associated with another entity.
-
E.
hasCommonSideEffect
Indicates that two or more treatments, drugs, or interventions share at least one side effect in common.
- F. None of above.
Provenance (3 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_69f349c2e3b88190a67834eb5bcffeaf |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffc704e1e88190884928a6a5c55a87 |
completed | May 9, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69ffc6b483d881908ad872e25fa6abc5 |
completed | May 9, 2026, 11:43 p.m. |
Created at: May 1, 2026, 1:59 a.m.