Triple

T3087883
Position Surface form Disambiguated ID Type / Status
Subject Central Maine Community College E64417 entity
Predicate abbreviation P43 FINISHED
Object CMCC
CMCC is a public community college in Auburn, Maine, offering two-year degree and certificate programs across a range of academic and technical fields.
 E326031 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: CMCC | Statement: [Central Maine Community College, abbreviation, CMCC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CMCC
Context triple: [Central Maine Community College, abbreviation, CMCC]
  • A. MCC
    MCC is a U.S. foreign aid agency that provides time-limited grants to promote economic growth, reduce poverty, and strengthen institutions in developing countries.
  • B. MCC
    MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
  • C. MNC
    MNC is the three-letter National Rail station code assigned to Markinch railway station in Fife, Scotland.
  • D. ZTE
    ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
  • E. Virgin Mobile
    Virgin Mobile is a wireless communications brand offering mobile phone services in multiple countries as part of Richard Branson’s broader Virgin Group.
  • 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: CMCC
Triple: [Central Maine Community College, abbreviation, CMCC]
Generated description
CMCC is a public community college in Auburn, Maine, offering two-year degree and certificate programs across a range of academic and technical fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CMCC
Target entity description: CMCC is a public community college in Auburn, Maine, offering two-year degree and certificate programs across a range of academic and technical fields.
  • A. MCC
    MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
  • B. MCC
    MCC is a U.S. foreign aid agency that provides time-limited grants to promote economic growth, reduce poverty, and strengthen institutions in developing countries.
  • C. MNC
    MNC is the three-letter National Rail station code assigned to Markinch railway station in Fife, Scotland.
  • D. ZTE
    ZTE is a major Chinese telecommunications and technology company known for manufacturing network equipment and smartphones and competing globally with firms like Nokia and Huawei.
  • E. Virgin Mobile
    Virgin Mobile is a wireless communications brand offering mobile phone services in multiple countries as part of Richard Branson’s broader Virgin Group.
  • 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_69ad857c97d88190b26f9b1c90839c77 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada209fd24819088d887de0a4158f4 completed March 8, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f8a1fdc48190ae1c2fb9e5198336 completed March 11, 2026, 11:20 p.m.
NEDg Description generation batch_69b1f9608e88819098f4044e54e0d908 completed March 11, 2026, 11:23 p.m.
NED2 Entity disambiguation (via description) batch_69b1fe3c8f408190988e7c7e3a51057e completed March 11, 2026, 11:43 p.m.
Created at: March 8, 2026, 3:03 p.m.