Triple

T9814907
Position Surface form Disambiguated ID Type / Status
Subject Mark Okerstrom E238376 entity
Predicate employer P7 FINISHED
Object Expedia Group E7140 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: Expedia Group | Statement: [Mark Okerstrom, employer, Expedia Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Expedia Group
Context triple: [Mark Okerstrom, employer, Expedia Group]
  • A. Expedia Group chosen
    Expedia Group is a leading American online travel and technology company that operates numerous global travel fare aggregators and travel metasearch engines.
  • B. Priceline
    Priceline is a major online travel agency known for offering discounted rates on flights, hotels, rental cars, and vacation packages.
  • C. Travelocity
    Travelocity is a major online travel agency that allows users to search for and book flights, hotels, rental cars, vacation packages, and other travel services.
  • D. 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.
  • E. Sabre Holdings
    Sabre Holdings is a major travel technology and global distribution systems company that provides software and services to airlines, hotels, and travel agencies 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f19660819083e3f15780352052 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc67db68819093217c9a74e72fbf completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:30 p.m.