Triple
T20759212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lumify |
E510928
|
entity |
| Predicate | avoidsEffect |
P17548
|
FINISHED |
| Object | rebound redness typical of some older vasoconstrictor drops (as marketed) |
—
|
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: rebound redness typical of some older vasoconstrictor drops (as marketed) | Statement: [Lumify, avoidsEffect, rebound redness typical of some older vasoconstrictor drops (as marketed)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: avoidsEffect Context triple: [Lumify, avoidsEffect, rebound redness typical of some older vasoconstrictor drops (as marketed)]
-
A.
avoidedConsequence
Indicates that an action or event prevented a particular consequence from occurring.
-
B.
designedToAvoid
chosen
Indicates that something was intentionally created or configured in a way that prevents or minimizes a particular outcome, condition, or interaction.
-
C.
seeksToAvoid
Indicates an entity’s intention or effort to stay away from, prevent, or not experience another entity or situation.
-
D.
noConfidenceEffect
Indicates that the subject’s lack of confidence does not produce any significant influence or change on the object or outcome.
-
E.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24751688190829f9d836abfb606 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:35 p.m.