Triple
T24405734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirty Deeds |
E615304
|
entity |
| Predicate | typicalImpact |
P103390
|
FINISHED |
| Object | DDT |
—
|
NE NERFINISHED |
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: DDT | Statement: [Dirty Deeds, typicalImpact, DDT]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalImpact Context triple: [Dirty Deeds, typicalImpact, DDT]
-
A.
typicalLevelOfInfluence
Indicates the usual degree or strength of influence one entity exerts over another or within a given context.
-
B.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
C.
impactDescription
chosen
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
D.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
E.
majorImpact
Indicates that one entity has a significant, highly influential, or transformative effect on another entity or outcome.
- 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_69e2d7e780bc81908049c779e697a7f6 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294dfd8d88190b831b6a8f4157980 |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.