Triple
T31709624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dee Baxter |
E809281
|
entity |
| Predicate | toneOfInteractions |
P7344
|
FINISHED |
| Object | mocking but ultimately friendly |
—
|
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: mocking but ultimately friendly | Statement: [Dee Baxter, toneOfInteractions, mocking but ultimately friendly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toneOfInteractions Context triple: [Dee Baxter, toneOfInteractions, mocking but ultimately friendly]
-
A.
tone
chosen
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
-
B.
contributesToTone
Indicates that one entity plays a role in shaping, influencing, or determining the overall tone or mood of another entity.
-
C.
inTonality
Indicates that something (such as a musical element, passage, or piece) is expressed, structured, or interpreted within a specific musical key or tonal framework.
-
D.
toneCategory
Indicates the tonal classification or type assigned to an entity, such as its pitch pattern, mood, or prosodic category.
-
E.
toneInSeries
Indicates the tonal quality or mood that characterizes a particular work within a series or the series as a whole.
- 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_69f348df4e048190a4a5a9932ada78d6 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:15 p.m.