Triple
T22214107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhenish pitch accent |
E549030
|
entity |
| Predicate | hasNumberOfContrasts |
P147319
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Rhenish pitch accent, hasNumberOfContrasts, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfContrasts Context triple: [Rhenish pitch accent, hasNumberOfContrasts, 2]
-
A.
hasVolumeContrasts
Indicates that an entity exhibits notable differences in loudness or intensity across its parts or over time.
-
B.
hasNumberOfColors
Indicates the quantity of distinct colors associated with an entity.
-
C.
hasDensityContrast
Indicates that one entity differs from another in material density, highlighting a contrast in how compact or dense they are.
-
D.
hasMainContrast
Indicates a primary opposing or differing relationship between two elements, highlighting the main point of contrast between them.
-
E.
providesContrastWith
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
- 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_69e11e3f7e04819089806d81d5ac431e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b8b13f8819099ed8bebbfea3bc8 |
completed | April 28, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69e71b4dcc408190a30429fb08fcf39e |
completed | April 21, 2026, 6:38 a.m. |
| PDg | Predicate description generation | batch_69e723f65c5c8190a0ee3c539e5d0767 |
completed | April 21, 2026, 7:15 a.m. |
Created at: April 16, 2026, 8:37 p.m.