Triple

T2870294
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Law, University of Cambridge E63543 entity
Predicate offersProgram P178 FINISHED
Object MCL
MCL is a specialized postgraduate law degree at the University of Cambridge focused on corporate and commercial law.
 E305590 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: MCL | Statement: [Faculty of Law, University of Cambridge, offersProgram, MCL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MCL
Context triple: [Faculty of Law, University of Cambridge, offersProgram, MCL]
  • A. LCL
    LCL is a visual component framework used by the Lazarus IDE to build cross-platform graphical user interfaces in Free Pascal.
  • B. MCA
    MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
  • C. MCA
    MCA is a prominent Algerian football club based in Algiers, officially known as Mouloudia Club d'Alger.
  • D. MCA
    MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
  • E. MCG
    MCG is a world-famous sports stadium in Melbourne, Australia, renowned as a premier venue for cricket and Australian rules football and for hosting major international sporting events.
  • 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: MCL
Triple: [Faculty of Law, University of Cambridge, offersProgram, MCL]
Generated description
MCL is a specialized postgraduate law degree at the University of Cambridge focused on corporate and commercial law.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MCL
Target entity description: MCL is a specialized postgraduate law degree at the University of Cambridge focused on corporate and commercial law.
  • A. LCL
    LCL is a visual component framework used by the Lazarus IDE to build cross-platform graphical user interfaces in Free Pascal.
  • B. MCA
    MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
  • C. MCA
    MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
  • D. MCA
    MCA is a prominent Algerian football club based in Algiers, officially known as Mouloudia Club d'Alger.
  • E. MCG
    MCG is a world-famous sports stadium in Melbourne, Australia, renowned as a premier venue for cricket and Australian rules football and for hosting major international sporting events.
  • 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfe2dcb48190a194253e733d14af completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01db01d348190945ab982ce5c5b2d completed March 10, 2026, 1:33 p.m.
NEDg Description generation batch_69b0201470cc81909188573c3749dffb completed March 10, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_69b020aa00888190a683a621f1e1a107 completed March 10, 2026, 1:46 p.m.
Created at: March 6, 2026, 10:02 p.m.