Triple

T19531757
Position Surface form Disambiguated ID Type / Status
Subject Hamming distance E488672 entity
Predicate field P3 FINISHED
Object computer science NE NERFINISHED

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: computer science | Statement: [Hamming distance, field, computer science]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: computer science
Context triple: [Hamming distance, field, computer science]
  • A. computer science chosen
    Computer science is the academic and practical field that studies computation, algorithms, data structures, and the design and analysis of hardware and software systems.
  • B. CS
    CS is the common abbreviation for the Church of Christ, Scientist, a Christian denomination founded by Mary Baker Eddy that emphasizes spiritual healing and the study of Christian Science.
  • C. CS
    CS is the common abbreviation for the Climax Series, a postseason playoff system used in Japan’s professional baseball leagues to determine league champions.
  • D. CS
    CS is the commonly used abbreviation and stock ticker for Credit Suisse, the former major Swiss multinational investment bank and financial services company.
  • E. CS
    CS is the abbreviation for Convergencia Social, a Chilean left-wing political party.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6363fd1f8819080805346efad2579 completed April 20, 2026, 2:20 p.m.
Created at: April 10, 2026, 1:41 p.m.