Triple

T17426546
Position Surface form Disambiguated ID Type / Status
Subject 162173 Ryugu E423752 entity
Predicate discoverer P412 FINISHED
Object LINEAR NE NERFINISHED

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: LINEAR | Statement: [162173 Ryugu, discoverer, LINEAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LINEAR
Context triple: [162173 Ryugu, discoverer, LINEAR]
  • A. LINEAR chosen
    LINEAR (Lincoln Near-Earth Asteroid Research) is an automated survey program that uses ground-based telescopes to discover and track near-Earth objects such as asteroids and comets.
  • B. A line
    The A line is a major New York City Subway service that runs primarily along the Eighth Avenue Line in Manhattan and extends into Brooklyn and Queens.
  • C. LIN
    LIN is the three-letter IATA airport code for Milan Linate Airport, one of the main airports serving Milan, Italy.
  • D. 1 Line
    The 1 Line is a light rail route in the Seattle metropolitan area that forms the core north–south spine of Sound Transit's Link light rail system.
  • E. Line L
    Line L is a cable car line of the Medellín Metro system that serves hillside neighborhoods by connecting them to the main urban transit network.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e448fcbf54819091babed0b9b05716 completed April 19, 2026, 3:16 a.m.
Created at: April 10, 2026, 5:46 a.m.