Triple

T1621096
Position Surface form Disambiguated ID Type / Status
Subject Surface RT E35031 entity
Predicate brand P1500 FINISHED
Object Surface E5695 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: Surface | Statement: [Surface RT, brand, Surface]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Surface
Context triple: [Surface RT, brand, Surface]
  • A. Surface chosen
    Surface is Microsoft's line of touchscreen-based personal computing devices, including laptops, tablets, and 2-in-1 hybrids.
  • B. Surfacing
    Surfacing is a 1972 novel by Margaret Atwood that blends psychological mystery with feminist and environmental themes as it follows a woman’s search for her missing father in rural Quebec.
  • C. Surf
    Surf is a critically acclaimed 2015 collaborative hip-hop and jazz-influenced album by Donnie Trumpet & The Social Experiment, prominently featuring Chance the Rapper.
  • D. Subsurface
    Subsurface is an open-source dive log and planning software application originally developed by Linux creator Linus Torvalds for recreational and technical scuba divers.
  • E. Lisse
    Lisse is a town in the western Netherlands renowned for its flower bulb fields and the famous Keukenhof gardens.
  • 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_69a886023194819080a3fccd6e325d0e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909b1fc788190b38c0aa4ccc2e953 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad6092fdd0819099bde0004de869c4 completed March 8, 2026, 11:42 a.m.
Created at: March 4, 2026, 7:28 p.m.