Triple

T11003341
Position Surface form Disambiguated ID Type / Status
Subject Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation E260052 entity
Predicate preNeuralMTContext P36 FINISHED
Object designed to augment phrase-based statistical machine translation systems 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: designed to augment phrase-based statistical machine translation systems | Statement: [Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation, preNeuralMTContext, designed to augment phrase-based statistical machine translation systems]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: preNeuralMTContext
Context triple: [Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation, preNeuralMTContext, designed to augment phrase-based statistical machine translation systems]
  • A. context chosen
    Indicates that one entity provides the surrounding circumstances, setting, or background within which another entity, event, or statement occurs or is interpreted.
  • B. pretext
    Indicates that one party uses a stated reason or excuse to conceal their true motive for an action or decision.
  • C. preStatePrecursor
    Indicates that one state or condition serves as a precursor to, or exists immediately before, another state in a process or sequence.
  • D. pretrainingRole
    Indicates the role or function an entity serves specifically during a pretraining phase or process.
  • E. previousLabelContext
    Indicates that something occurs or is defined in the context of the label that immediately precedes it in sequence or structure.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797546f448190946ee6442d657dc5 completed April 9, 2026, 12:11 p.m.
PD Predicate disambiguation batch_69d72e96be6c8190a46c69f61b2d8cd4 completed April 9, 2026, 4:44 a.m.
Created at: April 8, 2026, 9:25 p.m.