Triple
T5820908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Father Benedict |
E129103
|
entity |
| Predicate | toneContext |
P48342
|
FINISHED |
| Object | dark narrative |
—
|
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: dark narrative | Statement: [Father Benedict, toneContext, dark narrative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toneContext Context triple: [Father Benedict, toneContext, dark narrative]
-
A.
tone
Indicates the characteristic attitude or emotional quality expressed in how something is communicated or presented.
-
B.
tonalCenter
Indicates that one musical element functions as the primary pitch or key center around which another musical element is organized.
-
C.
tonalCharacteristic
Indicates the specific quality or character of a sound’s tone, such as its color, texture, or expressive nuance, in relation to an entity.
-
D.
toneAroundCharacter
chosen
Indicates the emotional or stylistic tone expressed in the narrative or dialogue surrounding a specific character.
-
E.
toneMarkFunction
Indicates a function or role that assigns, modifies, or interprets tone marks in a tonal or phonetic system.
- 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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.