Triple

T23075530
Position Surface form Disambiguated ID Type / Status
Subject Derek J. de Solla Price E575319 entity
Predicate knownFor P22 FINISHED
Object Price’s law of scientific productivity
Price’s law of scientific productivity is a bibliometric principle stating that a small fraction of researchers in a field produce a disproportionately large share of the total scientific output.
E1569174 NE FINISHED

How this triple was built (4 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: Price’s law of scientific productivity | Statement: [Derek J. de Solla Price, knownFor, Price’s law of scientific productivity]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Price’s law of scientific productivity
Context triple: [Derek J. de Solla Price, knownFor, Price’s law of scientific productivity]
  • A. Matthew effect in science
    The Matthew effect in science is a sociological concept describing how well-known scientists often receive disproportionately more credit and recognition than lesser-known researchers for similar work, reinforcing existing inequalities in scientific prestige and resources.
  • B. Source Normalized Impact per Paper
    Source Normalized Impact per Paper (SNIP) is a bibliometric indicator that measures a journal’s contextual citation impact by accounting for differences in citation practices across scientific fields.
  • C. The Business of Science
    The Business of Science is a book by engineer and entrepreneur Simon Ramo that explores how scientific and technical expertise intersect with management, industry, and practical problem-solving in the modern economy.
  • D. Drucker stability postulate
    The Drucker stability postulate is a fundamental criterion in plasticity theory that asserts materials must not exhibit negative incremental work, ensuring stable and physically realistic material behavior under loading.
  • E. Tactics of Scientific Research
    Tactics of Scientific Research is a foundational methodological text in experimental psychology and behavior analysis that outlines rigorous strategies for designing, conducting, and interpreting scientific experiments.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Price’s law of scientific productivity
Triple: [Derek J. de Solla Price, knownFor, Price’s law of scientific productivity]
Generated description
Price’s law of scientific productivity is a bibliometric principle stating that a small fraction of researchers in a field produce a disproportionately large share of the total scientific output.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Price’s law of scientific productivity
Target entity description: Price’s law of scientific productivity is a bibliometric principle stating that a small fraction of researchers in a field produce a disproportionately large share of the total scientific output.
  • A. Matthew effect in science
    The Matthew effect in science is a sociological concept describing how well-known scientists often receive disproportionately more credit and recognition than lesser-known researchers for similar work, reinforcing existing inequalities in scientific prestige and resources.
  • B. Source Normalized Impact per Paper
    Source Normalized Impact per Paper (SNIP) is a bibliometric indicator that measures a journal’s contextual citation impact by accounting for differences in citation practices across scientific fields.
  • C. The Business of Science
    The Business of Science is a book by engineer and entrepreneur Simon Ramo that explores how scientific and technical expertise intersect with management, industry, and practical problem-solving in the modern economy.
  • D. Drucker stability postulate
    The Drucker stability postulate is a fundamental criterion in plasticity theory that asserts materials must not exhibit negative incremental work, ensuring stable and physically realistic material behavior under loading.
  • E. Tactics of Scientific Research
    Tactics of Scientific Research is a foundational methodological text in experimental psychology and behavior analysis that outlines rigorous strategies for designing, conducting, and interpreting scientific experiments.
  • F. None of above. chosen

Provenance (5 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_69e245be28d48190ad1348d5a73db37d completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18c62c200819099c92654493288ad completed April 29, 2026, 4:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c15aaf74881909d2cd5f3d730f1b4 completed May 19, 2026, 7:47 a.m.
NEDg Description generation batch_6a0c15f186208190889e0766ddf03343 completed May 19, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_6a0c165b716c8190b1c1e1683fe897db completed May 19, 2026, 7:50 a.m.
Created at: April 17, 2026, 3:56 p.m.