Triple
T17610638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Teacher (Gregory of Nyssa’s writings) |
E428955
|
entity |
| Predicate | modeOfPresentation |
P107229
|
FINISHED |
| Object | dialogue |
—
|
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: dialogue | Statement: [The Teacher (Gregory of Nyssa’s writings), modeOfPresentation, dialogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeOfPresentation Context triple: [The Teacher (Gregory of Nyssa’s writings), modeOfPresentation, dialogue]
-
A.
presentedInFormat
Indicates that something is expressed, delivered, or made available using a particular format or representation.
-
B.
expositionMode
chosen
Indicates the manner or format in which information, narrative, or content is presented or explained.
-
C.
presentedIn
Indicates that something is shown, displayed, or formally introduced within a particular context, medium, event, or setting.
-
D.
displayMode
Indicates how content or information is visually presented or arranged to the user.
-
E.
hasPresentation
Indicates that an entity delivers, contains, or is associated with a specific presentation (such as a talk, slide deck, or formal display of information).
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2d294881908380b2ab0b4d2503 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 5:51 a.m.