Triple
T18962133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pretender |
E463937
|
entity |
| Predicate | featuresLoudQuietContrast |
P133961
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Pretender, featuresLoudQuietContrast, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresLoudQuietContrast Context triple: [The Pretender, featuresLoudQuietContrast, true]
-
A.
noiseReductionFeature
Indicates that an entity includes or supports a capability to reduce or minimize unwanted noise.
-
B.
achievesContrast
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
-
C.
contrastCapability
Indicates a relationship where one entity’s capabilities are compared or set in opposition to another’s, highlighting differences in what they can do or achieve.
-
D.
hasVariableBrightness
Indicates that the brightness of an entity is not constant but changes over time or under different conditions.
-
E.
brightnessVariation
Indicates a change or fluctuation in the level of brightness of an entity over time or across conditions.
- F. None of above. chosen
Provenance (4 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d5d368488190b0c7489335e5dd91 |
completed | April 20, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, noon