Triple
T8241067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cleinias |
E192534
|
entity |
| Predicate | hasDialogueForm |
P31331
|
FINISHED |
| Object | question-and-answer |
—
|
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: question-and-answer | Statement: [Cleinias, hasDialogueForm, question-and-answer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialogueForm Context triple: [Cleinias, hasDialogueForm, question-and-answer]
-
A.
hasDialogueFunction
Indicates that an utterance or segment of discourse serves a specific communicative role or function within a dialogue (e.g., question, answer, request, acknowledgment).
-
B.
dialogueForm
chosen
Indicates that one entity takes the form or structure of a dialogue, typically involving conversational or interactive exchange between parties.
-
C.
hasProseDialogue
Indicates that one entity contains or features spoken or conversational content expressed in prose form involving another entity.
-
D.
dialogueType
Indicates the specific kind or category of dialogue occurring between entities (e.g., question-answer, negotiation, instruction).
-
E.
hasNoSpokenDialogue
Indicates that the referenced entity does not produce any spoken dialogue within the given context or work.
- 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_69ca82dc8f148190a2c75a98501a7b91 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb783e13648190abf34eb8c244ea17 |
completed | March 31, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:47 p.m.