Triple

T4614160
Position Surface form Disambiguated ID Type / Status
Subject Match Group E100826 entity
Predicate operatedPlatform P1292 FINISHED
Object Hinge E455750 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: Hinge | Statement: [Match Group, operatedPlatform, Hinge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hinge
Context triple: [Match Group, operatedPlatform, Hinge]
  • A. Hinge chosen
    Hinge is a dating app designed to foster serious, long-term relationships by encouraging users to build detailed profiles and engage in more meaningful conversations.
  • B. Matchmakers
    Matchmakers is a popular Ukrainian comedy television series produced by Kvartal 95 Studio that follows the humorous clashes and relationships between two very different families.
  • C. Lovehunter
    Lovehunter is a 1979 hard rock album by British band Whitesnake, noted for its bluesy sound and controversial cover art.
  • D. The Perfect Match
    The Perfect Match is a romantic comedy film produced by Flavor Unit Entertainment that follows a commitment-phobic bachelor whose views on love are challenged by an unexpected relationship.
  • E. Duo
    Duo is a Google-developed video calling application designed for simple, high-quality one-to-one and group conversations across mobile and web platforms.
  • 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_69bd43cf363c819087fd5ab441b4a3f4 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6234e8108190b985270b9ddd1f3a completed March 20, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be035629248190a8723b5f1f9e57bc completed March 21, 2026, 2:32 a.m.
Created at: March 20, 2026, 1:12 p.m.