Triple
T8885265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vice Principal Douglas Panch |
E211512
|
entity |
| Predicate | toneWhenPronouncingWords |
P7344
|
FINISHED |
| Object | matter-of-fact |
—
|
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: matter-of-fact | Statement: [Vice Principal Douglas Panch, toneWhenPronouncingWords, matter-of-fact]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toneWhenPronouncingWords Context triple: [Vice Principal Douglas Panch, toneWhenPronouncingWords, matter-of-fact]
-
A.
typeOfPronunciationDescribed
Indicates that one entity specifies or characterizes the kind or style of pronunciation associated with another entity.
-
B.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
C.
isMorePronouncedIn
Indicates that a particular feature, quality, or effect appears with greater intensity or prominence in one context, entity, or condition than in another.
-
D.
tonalCharacteristic
Indicates the specific quality or character of a sound’s tone, such as its color, texture, or expressive nuance, in relation to an entity.
-
E.
tone
chosen
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc616cf8c48190a27b381e48f23377 |
completed | April 1, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:53 p.m.