Triple
T32512239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Squeaky-Voiced Teen |
E830966
|
entity |
| Predicate | typicalDialogueTrait |
P85534
|
FINISHED |
| Object | voice cracks frequently |
—
|
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: voice cracks frequently | Statement: [Squeaky-Voiced Teen, typicalDialogueTrait, voice cracks frequently]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDialogueTrait Context triple: [Squeaky-Voiced Teen, typicalDialogueTrait, voice cracks frequently]
-
A.
typicalDialogueStyle
Indicates the characteristic manner or pattern in which an entity typically communicates or conducts dialogue.
-
B.
characteristicDialogue
Indicates that one entity is known for or strongly associated with a particular style, pattern, or type of dialogue in relation to another entity.
-
C.
typicalDialogueTheme
Indicates the usual or characteristic subject matter that conversations or dialogues between the entities tend to focus on.
-
D.
hasDialogueTrait
chosen
Indicates that an entity possesses a specific characteristic or quality related to dialogue or conversational behavior.
-
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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1 a.m.