Triple

T9142599
Position Surface form Disambiguated ID Type / Status
Subject MS E219365 entity
Predicate contrastWith P278 FINISHED
Object MEng E80622 NE FINISHED

How this triple was built (2 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: MEng | Statement: [MS, contrastWith, MEng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MEng
Context triple: [MS, contrastWith, MEng]
  • A. Master of Engineering chosen
    The Master of Engineering is a postgraduate professional degree focused on advanced engineering coursework and applied research, preparing graduates for specialized technical careers or further doctoral studies.
  • B. CEng
    CEng is the professional post-nominal title used by Chartered Engineers, typically signifying a high level of competence and recognition in engineering.
  • C. ENGM
    ENGM is the ICAO airport code for Oslo Airport, Gardermoen, the main international airport serving Norway’s capital region.
  • D. Doctor of Engineering
    Doctor of Engineering is an advanced doctoral degree in engineering that recognizes significant original research and expertise in engineering disciplines.
  • E. BSEE
    BSEE is a U.S. federal agency within the Department of the Interior responsible for overseeing safety and environmental protection in offshore oil and gas operations.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca83e012288190a5771058adbaabd2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8f5f740819098236ada5b95889d completed April 1, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d048186cc88190be4f515c16c20450 completed April 3, 2026, 11:07 p.m.
Created at: March 30, 2026, 7:19 p.m.