Triple
T32512142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribwich |
E830963
|
entity |
| Predicate | causesEffect |
P106972
|
FINISHED |
| Object | addictive behavior in consumers |
—
|
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: addictive behavior in consumers | Statement: [Ribwich, causesEffect, addictive behavior in consumers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causesEffect Context triple: [Ribwich, causesEffect, addictive behavior in consumers]
-
A.
providesEffect
chosen
Indicates that one entity causes, delivers, or produces a particular effect or outcome on another entity.
-
B.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
C.
hasDirectEffect
Indicates that one entity produces an immediate and unmediated impact or change on another entity.
-
D.
capturesEffectOf
Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
-
E.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 1, 2026, 1 a.m.