Triple

T6508728
Position Surface form Disambiguated ID Type / Status
Subject Expo 93 E150074 entity
Predicate BIECategory P38490 FINISHED
Object Specialized Expo E271986 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: Specialized Expo | Statement: [Expo 93, BIECategory, Specialized Expo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Specialized Expo
Context triple: [Expo 93, BIECategory, Specialized Expo]
  • A. Specialised Expos chosen
    Specialised Expos are internationally sanctioned, theme-focused world exhibitions that are smaller and shorter in duration than Universal Expos and must adhere to rules set by the Bureau International des Expositions.
  • B. Expo
    Expo is an open-source platform and toolchain for building, deploying, and iterating on React Native applications.
  • C. Expo
    Expo is a popular brand best known for its dry-erase markers and related whiteboard accessories commonly used in schools, offices, and homes.
  • D. Reed Exhibitions
    Reed Exhibitions is a global events and trade show organizer known for producing large-scale exhibitions and conferences across diverse industries worldwide.
  • E. Helexpo
    Helexpo is Greece’s national exhibition and conference organizer, best known for staging major trade fairs and events such as the Thessaloniki International Fair.
  • 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_69c687ef291081909d437f035eef1cda completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69f386aa08190bfc8592a92ec6339 completed March 27, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb5782fc8190a56b714bbc007490 completed March 27, 2026, 6:24 p.m.
Created at: March 27, 2026, 1:43 p.m.