Triple
T21907512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sprechstimme |
E540976
|
entity |
| Predicate | usedForEffect |
P98
|
FINISHED |
| Object | heightened expressivity |
—
|
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: heightened expressivity | Statement: [Sprechstimme, usedForEffect, heightened expressivity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForEffect Context triple: [Sprechstimme, usedForEffect, heightened expressivity]
-
A.
usedFor
chosen
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
B.
usesEffectType
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
C.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
D.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
-
E.
providesEffect
Indicates that one entity causes, delivers, or produces a particular effect or outcome on another entity.
- 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_69e0c47b4e8c81908c8076eaa4c8e4f2 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f121d806688190b23502aacbfde4bd |
completed | April 28, 2026, 9:08 p.m. |
| PD | Predicate disambiguation | batch_69e6be9ebf4c8190892df1a8e1313f88 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 7:38 p.m.