Triple

T804938
Position Surface form Disambiguated ID Type / Status
Subject Honey Science LLC E17409 entity
Predicate product P490 FINISHED
Object Honey mobile app E17409 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: Honey mobile app | Statement: [Honey Science LLC, product, Honey mobile app]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Honey mobile app
Context triple: [Honey Science LLC, product, Honey mobile app]
  • A. Honey Science LLC chosen
    Honey Science LLC is a technology company best known for its browser extension that automatically finds and applies online shopping coupon codes and discounts.
  • B. Breeze Mobile
    Breeze Mobile is a mobile ticketing and payment app used by the Metropolitan Atlanta Rapid Transit Authority (MARTA) for accessing public transit services in the Atlanta area.
  • C. Honey, Honey
    "Honey, Honey" is a catchy pop song by the Swedish group ABBA, featured prominently in the musical and film adaptation of *Mamma Mia!* as one of its early ensemble numbers.
  • D. Honeycomb
    "Honeycomb" is a popular 1957 pop song recorded by American singer Jimmie Rodgers that became one of his signature hits.
  • E. Bee Network
    Bee Network is Greater Manchester’s integrated public transport system brand, unifying buses, trams, cycling and walking under a single, coordinated network.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aabff3d88190bec4299fa0d87df0 completed March 1, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69a68926c04081908923a7d114d1842d completed March 3, 2026, 7:09 a.m.
Created at: March 1, 2026, 7:38 p.m.