Triple

T15095900
Position Surface form Disambiguated ID Type / Status
Subject Greg Maffei E360535 entity
Predicate boardMemberOf P10 FINISHED
Object TripAdvisor E597251 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: TripAdvisor | Statement: [Greg Maffei, boardMemberOf, TripAdvisor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TripAdvisor
Context triple: [Greg Maffei, boardMemberOf, TripAdvisor]
  • A. TripAdvisor chosen
    TripAdvisor is a popular online travel platform that provides user-generated reviews, ratings, and booking tools for hotels, restaurants, and attractions worldwide.
  • B. Booking.com
    Booking.com is a major global online travel agency that allows users to search for and book accommodations such as hotels, apartments, and vacation rentals.
  • C. Angie’s List
    Angie’s List is an online marketplace and review platform where consumers can find and rate local service professionals such as contractors, plumbers, and other home service providers.
  • D. Agoda
    Agoda is a global online travel agency known for offering hotel and accommodation bookings, flights, and travel services, particularly strong in the Asia-Pacific region.
  • E. Yelp
    Yelp is an online platform that hosts user-generated reviews and ratings of local businesses such as restaurants, shops, 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005466e9c8190a68e1fbeb8922b1a completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae21134c81908939ad6ce46703d8 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:04 a.m.