Triple
T8510857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Χαρμίδης |
E201447
|
entity |
| Predicate | dialogueNumbering |
P81096
|
FINISHED |
| Object | Stephanus pagination 153a–176d |
—
|
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: Stephanus pagination 153a–176d | Statement: [Χαρμίδης, dialogueNumbering, Stephanus pagination 153a–176d]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dialogueNumbering Context triple: [Χαρμίδης, dialogueNumbering, Stephanus pagination 153a–176d]
-
A.
numberOfDialogues
Indicates the total count of dialogues associated with or occurring between the referenced entities.
-
B.
dialogueSection
chosen
Indicates a specific segment or portion within a larger dialogue or conversational exchange.
-
C.
dialoguePosition
Indicates the relative placement or ordering of an utterance or turn within a dialogue or conversational sequence.
-
D.
dialogueLevel
Indicates the degree or intensity of conversational interaction occurring between entities.
-
E.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
- 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_69ca8320e5748190ac2c585a0bba8193 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe608e5b08190a6d551793e8ed94b |
completed | March 31, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:15 p.m.