Triple

T2553501
Position Surface form Disambiguated ID Type / Status
Subject EXPE E56679 entity
Predicate associatedBrand P1500 FINISHED
Object trivago E56681 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: trivago | Statement: [EXPE, associatedBrand, trivago]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: trivago
Context triple: [EXPE, associatedBrand, trivago]
  • A. trivago chosen
    trivago is a global hotel and accommodation metasearch platform that compares prices from numerous booking sites to help users find and book lodging deals.
  • B. TripSavvy
    TripSavvy is a travel-focused online publication offering destination guides, tips, and advice for travelers.
  • C. Wotif Group
    Wotif Group is an online travel company best known for its hotel and accommodation booking platforms, particularly in the Australian and Asia-Pacific markets.
  • D. easyHotel
    easyHotel is a UK-based budget hotel chain offering no-frills, low-cost accommodation, primarily in city-center locations across Europe and beyond.
  • E. Vrbo
    Vrbo is a vacation rental marketplace that connects travelers with owners and property managers offering homes, condos, cabins, and other short-term lodging options worldwide.
  • 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_69ab4a4bfec081908039988ec4c86e28 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd30bc6388190b78f2f931eb54041 completed March 7, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5d17ecd0819097c6b95307cc7557 completed March 9, 2026, 11:51 p.m.
Created at: March 6, 2026, 9:48 p.m.