Triple
T21652693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Varjak |
E534376
|
entity |
| Predicate | romanticGenreTrope |
P118894
|
FINISHED |
| Object | reforming playgirl through love |
—
|
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: reforming playgirl through love | Statement: [Paul Varjak, romanticGenreTrope, reforming playgirl through love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticGenreTrope Context triple: [Paul Varjak, romanticGenreTrope, reforming playgirl through love]
-
A.
romanticPattern
chosen
Indicates a recurring style, tendency, or structure in how romantic relationships or attractions develop or are expressed between entities.
-
B.
romanticArc
Indicates a developing or ongoing romantic relationship or storyline between the involved entities.
-
C.
romanticTragedy
Indicates a relationship where a romantic involvement between entities leads to or is characterized by tragic or sorrowful outcomes.
-
D.
romanticSubplotCentral
Indicates that a romantic subplot is a primary, driving element of the narrative rather than a minor or peripheral thread.
-
E.
romanticallyObsessedWith
Indicates a strong, often overwhelming romantic fixation or preoccupation that one entity has toward another.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:36 p.m.