Triple
T448807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phaedo |
E7081
|
entity |
| Predicate | dialogueStyle |
P5869
|
FINISHED |
| Object | dramatic |
—
|
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: dramatic | Statement: [Phaedo, dialogueStyle, dramatic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialogueStyle Context triple: [Phaedo, dialogueStyle, dramatic]
-
A.
dialogueWith
Indicates that two entities are engaged in a mutual conversational exchange or dialogue with each other.
-
B.
narrativeStyle
chosen
Indicates how a narrative is told, such as the point of view, tone, and structural approach used to present a story or account.
-
C.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
-
D.
communicationMode
Indicates the method or channel through which communication between entities is carried out.
-
E.
typicalSpeaker
Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
- 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef6755a08190a057e72279b70456 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2ede1a1108190a4a06b3416ae6156 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.