Triple

T12798004
Position Surface form Disambiguated ID Type / Status
Subject Carnap's continuum of inductive methods E305938 entity
Predicate aimsToCapture P106453 FINISHED
Object rational learning from experience 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: rational learning from experience | Statement: [Carnap's continuum of inductive methods, aimsToCapture, rational learning from experience]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: aimsToCapture
Context triple: [Carnap's continuum of inductive methods, aimsToCapture, rational learning from experience]
  • A. aimOfAttacker
    Indicates that a particular goal, target, or objective is what the attacker intends to achieve or affect.
  • B. aimsToControl
    Indicates an intention or effort by one entity to gain power over, direct, or regulate another entity or situation.
  • C. aimsToEliminate
    Indicates an intention or directed effort by one entity to remove, destroy, or completely get rid of another entity or condition.
  • D. aimOf
    Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
  • E. aimedAtBy
    Indicates that one entity serves as the target or goal toward which another entity directs an action, intention, or focus.
  • F. None of above. chosen

Provenance (4 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6f858c8190915ede38e9a6a2df completed April 10, 2026, 9:41 p.m.
PD Predicate disambiguation batch_69d9640ed7448190b276e7fab649f7d2 completed April 10, 2026, 8:56 p.m.
PDg Predicate description generation batch_69d96d88be0481908c311f1e71b61e70 completed April 10, 2026, 9:37 p.m.
Created at: April 9, 2026, 5:30 p.m.