Triple

T672929
Position Surface form Disambiguated ID Type / Status
Subject ACS Nano E13011 entity
Predicate subjectArea P3 FINISHED
Object Science E53325 NE 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: Science | Statement: [ACS Nano, subjectArea, Science]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Science
Context triple: [ACS Nano, subjectArea, Science]
  • A. Science chosen
    Science is a leading peer-reviewed academic journal that publishes cutting-edge research across a wide range of scientific disciplines.
  • B. SCI
    SCI is the abbreviation for the Strategic Computing Initiative, a U.S. Defense Advanced Research Projects Agency (DARPA) program from the 1980s that aimed to advance artificial intelligence and high-performance computing for military applications.
  • C. SCI
    SCI is a widely used citation indexing service that tracks and analyzes references in leading scientific journals to assess research impact and influence.
  • D. Science and Technology
    Science and Technology is a scholarly publication focused on research, analysis, and commentary at the intersection of scientific innovation and technological development.
  • E. Science (journal)
    Science is a leading peer‑reviewed academic journal that publishes cutting-edge research across all scientific disciplines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a023753c8190900f26fa7698775b completed March 1, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c39f3e1481908f395cdb19cfd2fc completed March 2, 2026, 5:06 p.m.
Created at: March 1, 2026, 7:36 p.m.