Triple
T6239637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sally Brown (You're a Good Man, Charlie Brown) |
E139565
|
entity |
| Predicate | toneOfDialogue |
P7344
|
FINISHED |
| Object | humorous |
—
|
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: humorous | Statement: [Sally Brown (You're a Good Man, Charlie Brown), toneOfDialogue, humorous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toneOfDialogue Context triple: [Sally Brown (You're a Good Man, Charlie Brown), toneOfDialogue, humorous]
-
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.
voiceType
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
D.
isToneNeutral
Indicates that the tone of the referenced content is neither positive nor negative, but emotionally neutral or unbiased.
-
E.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
- 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063048df081909a13d16b6f6bf65d |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:23 p.m.