Triple
T2391915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yelena Belova |
E48961
|
entity |
| Predicate | enhancement |
P3261
|
FINISHED |
| Object | Red Room conditioning |
—
|
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: Red Room conditioning | Statement: [Yelena Belova, enhancement, Red Room conditioning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enhancement Context triple: [Yelena Belova, enhancement, Red Room conditioning]
-
A.
improvesOn
Indicates that one entity enhances, refines, or performs better than another entity, typically by addressing its limitations or increasing its effectiveness.
-
B.
strengthens
chosen
Indicates that one entity increases the power, effectiveness, or resilience of another.
-
C.
phase2Enhancement
Indicates that an entity is involved in or associated with the second phase of an enhancement or improvement process.
-
D.
extension
Indicates that one entity is a lengthening, continuation, or added part of another entity beyond its original limits.
-
E.
increases
Indicates that one entity causes another entity’s value, level, or intensity to become larger or higher.
- 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_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc87587708190a7f2bc473a898bc2 |
completed | March 7, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69abc5a1b5748190b4cd8989700f4dd2 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.