Triple

T6494943
Position Surface form Disambiguated ID Type / Status
Subject Spencer Rascoff E148132 entity
Predicate employer P7 FINISHED
Object Expedia 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 | Statement: [Spencer Rascoff, employer, Expedia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Expedia
Context triple: [Spencer Rascoff, employer, Expedia]
  • 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. 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.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06ab7c0b8819091437a293b40dfd2 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653c21f948190989da451bc573b4d completed March 27, 2026, 9:54 a.m.
Created at: March 22, 2026, 4:53 p.m.