Triple
T14704793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vandover and the Brute |
E345397
|
entity |
| Predicate | hasBruteElement |
P115427
|
FINISHED |
| Object | animalistic side of the protagonist |
—
|
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: animalistic side of the protagonist | Statement: [Vandover and the Brute, hasBruteElement, animalistic side of the protagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBruteElement Context triple: [Vandover and the Brute, hasBruteElement, animalistic side of the protagonist]
-
A.
hasElementType
Indicates that something is composed of or contains elements that are of a specified type.
-
B.
hasBronzeElement
Indicates that an entity includes or is associated with at least one element made of bronze.
-
C.
hasForensicElement
Indicates that something includes, involves, or is characterized by a forensic component, aspect, or feature.
-
D.
hasProgramElement
Indicates that one entity contains, includes, or is associated with a specific program element (such as a function, class, module, or code component).
-
E.
hasBracket
Indicates that one entity possesses, includes, or is associated with a bracket component or structure.
- F. None of above. chosen
Provenance (4 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb6086c608190a66c64e23a3e002f |
completed | April 14, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716d3aac8190aaa6dc1f099b86e8 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:28 a.m.