Triple
T7671539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meghnad Badh Kavya |
E173758
|
entity |
| Predicate | characterizationStyle |
P63040
|
FINISHED |
| Object | psychological depth |
—
|
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: psychological depth | Statement: [Meghnad Badh Kavya, characterizationStyle, psychological depth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterizationStyle Context triple: [Meghnad Badh Kavya, characterizationStyle, psychological depth]
-
A.
characterStyle
Indicates how a character is visually or typographically presented, such as its font, weight, size, or decorative attributes.
-
B.
rhetoricalStyle
Indicates the characteristic manner or technique of expression used in communication, such as tone, structure, and persuasive strategies.
-
C.
characterDescription
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
D.
characterizationFocus
chosen
Indicates that the primary emphasis or concern of a characterization is directed toward a particular aspect, feature, or dimension of the subject.
-
E.
styleDescribedAs
Indicates that the manner, aesthetic, or mode of something is characterized or labeled using a particular style description.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7063dab1881909598b04999b8b690 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015f7430819099d3ea2781b7cee2 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4 p.m.