Triple

T22710178
Position Surface form Disambiguated ID Type / Status
Subject LispWorks E561570 entity
Predicate supportsStandard P1587 FINISHED
Object MOP
MOP (Metaobject Protocol) is a reflective programming interface in Common Lisp that allows programmers to customize and extend the language’s object system at runtime.
E1550243 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: MOP | Statement: [LispWorks, supportsStandard, MOP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MOP
Context triple: [LispWorks, supportsStandard, MOP]
  • A. MOP
    MOP is the ISO 4217 currency code for the Macanese pataca, the official currency of Macau.
  • B. MOP
    MOP is the IATA airport code for Mount Pleasant Municipal Airport in Michigan, United States.
  • C. MOP
    MOP is the National Rail station code for Moor Park railway station in Hertfordshire, England.
  • D. MOP
    MOP is the governing body that brings together countries to review and make decisions on the implementation of the Cartagena Protocol on Biosafety.
  • E. MOP
    MOP is the commonly used acronym for Chile’s Ministry of Public Works, the government body responsible for planning, building, and maintaining the country’s public infrastructure.
  • 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: MOP
Triple: [LispWorks, supportsStandard, MOP]
Generated description
MOP (Metaobject Protocol) is a reflective programming interface in Common Lisp that allows programmers to customize and extend the language’s object system at runtime.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MOP
Target entity description: MOP (Metaobject Protocol) is a reflective programming interface in Common Lisp that allows programmers to customize and extend the language’s object system at runtime.
  • A. MOP
    MOP is the ISO 4217 currency code for the Macanese pataca, the official currency of Macau.
  • B. MOP
    MOP is the IATA airport code for Mount Pleasant Municipal Airport in Michigan, United States.
  • C. MOP
    MOP is the National Rail station code for Moor Park railway station in Hertfordshire, England.
  • D. MOP
    MOP is the governing body that brings together countries to review and make decisions on the implementation of the Cartagena Protocol on Biosafety.
  • E. MOP
    MOP is the commonly used acronym for Chile’s Ministry of Public Works, the government body responsible for planning, building, and maintaining the country’s public infrastructure.
  • 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_69e2454f1348819088d83f420925a5c1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f178d1e24881909ebd4531c0daef7f completed April 29, 2026, 3:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b7ed9cb908190b50dd5297ca2d17c completed May 18, 2026, 9:04 p.m.
NEDg Description generation batch_6a0b7fbb53388190b0942c28b5748c60 completed May 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_6a0b806b4e1481909babc97a8914947a completed May 18, 2026, 9:11 p.m.
Created at: April 17, 2026, 3:17 p.m.