Triple
T3056201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Divine Miss M |
E60485
|
entity |
| Predicate | featuresCoversOf |
P13946
|
FINISHED |
| Object | pop standards |
—
|
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: pop standards | Statement: [The Divine Miss M, featuresCoversOf, pop standards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCoversOf Context triple: [The Divine Miss M, featuresCoversOf, pop standards]
-
A.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
-
B.
alsoCovers
chosen
Indicates that something extends its scope or applicability to include an additional subject, area, or case beyond what was originally covered.
-
C.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
D.
eraCovered
Indicates that one entity temporally encompasses, includes, or spans the historical period or era associated with another entity.
-
E.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf7ebd48190ad5748a18fa9a56a |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962326e081909d5521c3d3ea3158 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.