Triple
T8423677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thrasyllan tetralogies |
E198923
|
entity |
| Predicate | hasTotalDialogues |
P59311
|
FINISHED |
| Object | 36 |
—
|
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: 36 | Statement: [Thrasyllan tetralogies, hasTotalDialogues, 36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTotalDialogues Context triple: [Thrasyllan tetralogies, hasTotalDialogues, 36]
-
A.
numberOfDialogues
chosen
Indicates the total count of dialogues associated with or occurring between the referenced entities.
-
B.
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).
-
C.
hasProseDialogue
Indicates that one entity contains or features spoken or conversational content expressed in prose form involving another entity.
-
D.
hasApproximateTotalSpeakers
Indicates that an entity is associated with an estimated or roughly calculated number of total speakers, rather than an exact count.
-
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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb859f787481908a11797a317c8849 |
completed | March 31, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.