Triple

T8021238
Position Surface form Disambiguated ID Type / Status
Subject 東京大学公共政策大学院 E186745 entity
Predicate shortName P43 FINISHED
Object GraSPP E186744 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: GraSPP | Statement: [東京大学公共政策大学院, shortName, GraSPP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GraSPP
Context triple: [東京大学公共政策大学院, shortName, GraSPP]
  • A. GraSPP chosen
    GraSPP is the Graduate School of Public Policy at the University of Tokyo, offering advanced education and research in public policy and related fields.
  • B. SPP
    SPP is the National Rail station code for Shippea Hill railway station in Cambridgeshire, England.
  • C. SPP
    SPP was the Mexican federal government’s Secretariat responsible for national economic planning, public spending, and budgetary policy.
  • D. SPP
    SPP is the Supreme People's Procuratorate of China, the highest national agency responsible for legal prosecution and supervision of law enforcement in the country.
  • E. SSAP
    SSAP (Source Service Access Point) is a field in IEEE 802.2 LLC headers that identifies the logical source endpoint of a network service access point for data link layer communications.
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3e8d90488190b57d1e748e272061 completed March 31, 2026, 3:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63c6a9208190841ed55b8c6ec73f completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:20 p.m.