Triple

T2452482
Position Surface form Disambiguated ID Type / Status
Subject Science E53737 entity
Predicate title P38 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: [Science, title, Science]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Science
Context triple: [Science, title, 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. Syience
    Syience is a music producer known for his work in contemporary R&B and pop, collaborating with prominent artists on charting tracks.
  • C. 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.
  • D. SCI
    SCI is a widely used citation indexing service that tracks and analyzes references in leading scientific journals to assess research impact and influence.
  • E. 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.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0f52524819088b00009c9dd1823 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17932530819097caefff366e2183 completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:43 p.m.