Triple

T7025149
Position Surface form Disambiguated ID Type / Status
Subject Brian Reid E162925 entity
Predicate notableWork P4 FINISHED
Object Scribe text processing system
The Scribe text processing system is an early, influential document preparation and formatting program developed by Brian Reid that pioneered many concepts later used in systems like LaTeX.
E636830 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: Scribe text processing system | Statement: [Brian Reid, notableWork, Scribe text processing system]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scribe text processing system
Context triple: [Brian Reid, notableWork, Scribe text processing system]
  • A. Kurzweil OCR (optical character recognition) systems
    Kurzweil OCR (optical character recognition) systems are pioneering software tools that convert printed text into digital, machine-readable form, widely used for document digitization and accessibility for the visually impaired.
  • B. “A Computer Program for Understanding Natural Language”
    “A Computer Program for Understanding Natural Language” is a landmark 1968 paper by Terry Winograd that presents an early natural language understanding system capable of interpreting and executing commands in a simulated blocks world.
  • C. Character repertoire description language (CREPDL)
    Character repertoire description language (CREPDL) is an ISO/IEC 19757-7 standard for formally specifying and validating sets of permitted characters in XML and related document formats.
  • D. On the Arrangement of Words
    On the Arrangement of Words is an ancient rhetorical treatise by Dionysius of Halicarnassus that analyzes how word order and stylistic choices affect the clarity, harmony, and persuasive power of prose.
  • E. CWEB literate programming system
    The CWEB literate programming system is a software tool created by Donald E. Knuth (with Silvio Levy) that integrates C or C++ source code with richly formatted documentation to produce both compilable programs and high-quality typeset descriptions.
  • 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: Scribe text processing system
Triple: [Brian Reid, notableWork, Scribe text processing system]
Generated description
The Scribe text processing system is an early, influential document preparation and formatting program developed by Brian Reid that pioneered many concepts later used in systems like LaTeX.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Scribe text processing system
Target entity description: The Scribe text processing system is an early, influential document preparation and formatting program developed by Brian Reid that pioneered many concepts later used in systems like LaTeX.
  • A. Kurzweil OCR (optical character recognition) systems
    Kurzweil OCR (optical character recognition) systems are pioneering software tools that convert printed text into digital, machine-readable form, widely used for document digitization and accessibility for the visually impaired.
  • B. “A Computer Program for Understanding Natural Language”
    “A Computer Program for Understanding Natural Language” is a landmark 1968 paper by Terry Winograd that presents an early natural language understanding system capable of interpreting and executing commands in a simulated blocks world.
  • C. Character repertoire description language (CREPDL)
    Character repertoire description language (CREPDL) is an ISO/IEC 19757-7 standard for formally specifying and validating sets of permitted characters in XML and related document formats.
  • D. On the Arrangement of Words
    On the Arrangement of Words is an ancient rhetorical treatise by Dionysius of Halicarnassus that analyzes how word order and stylistic choices affect the clarity, harmony, and persuasive power of prose.
  • E. CWEB literate programming system
    The CWEB literate programming system is a software tool created by Donald E. Knuth (with Silvio Levy) that integrates C or C++ source code with richly formatted documentation to produce both compilable programs and high-quality typeset descriptions.
  • 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_69c6885b26248190a857541e3d10e299 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1fb8f0c8190b15dd7ce7ab6a8f2 completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c77581e2a88190ad2ec9855772c6a5 completed March 28, 2026, 6:30 a.m.
NEDg Description generation batch_69c7768f12648190a8e9855af2458a94 completed March 28, 2026, 6:34 a.m.
NED2 Entity disambiguation (via description) batch_69c776bdf56c8190a9fa83d6f2697f1b completed March 28, 2026, 6:35 a.m.
Created at: March 27, 2026, 2:35 p.m.