Triple
T38648447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masochism: Coldness and Cruelty and Venus in Furs |
E938778
|
entity |
| Predicate | pairsWorkWith |
P115639
|
FINISHED |
| Object | Venus in Furs |
—
|
NE NERFINISHED |
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: Venus in Furs | Statement: [Masochism: Coldness and Cruelty and Venus in Furs, pairsWorkWith, Venus in Furs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pairsWorkWith Context triple: [Masochism: Coldness and Cruelty and Venus in Furs, pairsWorkWith, Venus in Furs]
-
A.
workPairing
chosen
Indicates that two entities are associated or grouped together for the purpose of working or collaborating on a task, project, or role.
-
B.
pairBond
Indicates a long-term, typically exclusive social or reproductive partnership formed between two individuals.
-
C.
commonPair
Indicates that two entities commonly occur together or are frequently associated as a pair in some shared context.
-
D.
partnerInWorkOf
Indicates a collaborative relationship where one entity works together with another on a shared task, project, or professional activity.
-
E.
starPairing
Indicates a relationship where two stars are associated or grouped together as a pair, typically for observational, analytical, or classificatory purposes.
- 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_69f76ed948ec81908ce7811608a8f359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.