Triple

T5983007
Position Surface form Disambiguated ID Type / Status
Subject National University of Mongolia E133162 entity
Predicate abbreviation P43 FINISHED
Object NUM E558013 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: NUM | Statement: [National University of Mongolia, abbreviation, NUM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NUM
Context triple: [National University of Mongolia, abbreviation, NUM]
  • A. NUM chosen
    NUM is a common abbreviation for the National University of Mongolia, the country’s oldest and largest public university and a leading center of higher education and research in Mongolia.
  • B. Numbers
    Numbers is Apple's spreadsheet application for macOS and iOS, used to create, analyze, and visualize data in tables and charts.
  • C. Numbers
    Numbers is the fourth book of the Hebrew Bible and the Christian Old Testament, recounting the Israelites’ wilderness wanderings and organizing laws and censuses.
  • D. N
    The N is a New York City Subway service that runs along the Broadway Line in Manhattan and connects Queens, Manhattan, and Brooklyn.
  • E. DIGIT
    DIGIT is the European Commission’s Directorate‑General responsible for shaping, implementing, and managing the EU institutions’ digital, IT, and cybersecurity strategies and services.
  • 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_69c0086f45e8819098f73dd16d45ec9d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a6a9f2c8190b900cd7e3ab9fe42 completed March 22, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1084e9ca481909f585b3d19991a60 completed March 23, 2026, 9:30 a.m.
Created at: March 22, 2026, 4:04 p.m.