Triple
T4293702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A3C |
E99656
|
entity |
| Predicate | usesLossComponent |
P31982
|
FINISHED |
| Object | policy loss |
—
|
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: policy loss | Statement: [A3C, usesLossComponent, policy loss]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLossComponent Context triple: [A3C, usesLossComponent, policy loss]
-
A.
usesLossFunction
chosen
Indicates that one entity employs a particular loss function as part of its optimization or learning process.
-
B.
usesPointsForLoss
Indicates that a system or rule assigns or deducts points to represent or account for a loss.
-
C.
usedComponent
Indicates that one entity has employed or incorporated another entity as a component in its structure, function, or operation.
-
D.
hasPartiallyLostUseOf
Indicates that an entity has experienced a reduction, but not a complete loss, in the functional use of another entity.
-
E.
lossType
Indicates the specific category or nature of a loss associated with an entity or event.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35082228081908504e3fd7c4ca1e8 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.