Triple
T6993304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proximal Policy Optimization |
E162136
|
entity |
| Predicate | objectiveContains |
P32133
|
FINISHED |
| Object | clipping term |
—
|
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: clipping term | Statement: [Proximal Policy Optimization, objectiveContains, clipping term]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: objectiveContains Context triple: [Proximal Policy Optimization, objectiveContains, clipping term]
-
A.
objectiveIncludes
chosen
Indicates that a broader objective encompasses or contains a specific sub-objective, component, or element as part of its scope.
-
B.
usesObjective
Indicates that an agent employs or applies a particular object, tool, or resource to carry out an action or achieve a goal.
-
C.
aimOf
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
D.
followsObjective
Indicates that one entity pursues, adheres to, or acts in accordance with the goal, plan, or objective defined by another entity.
-
E.
actorObjective
Indicates that an actor has a specific goal, purpose, or intended outcome in relation to another entity or situation.
- 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_69c68856d7808190ab33ee914640281b |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbc30fdc81909244d83c8178755c |
completed | March 27, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c4a18881908d267137daed828b |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:32 p.m.