Triple

T2270974
Position Surface form Disambiguated ID Type / Status
Subject Moscow tram network E50655 entity
Predicate hasDedicatedRightOfWay P31631 FINISHED
Object partially LITERAL 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: partially | Statement: [Moscow tram network, hasDedicatedRightOfWay, partially]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDedicatedRightOfWay
Context triple: [Moscow tram network, hasDedicatedRightOfWay, partially]
  • A. hasDedicatedLanes chosen
    Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
  • B. hasRightOfWay
    Indicates that one entity is entitled to proceed or act before another in a shared space or interaction, without having to yield.
  • C. hasWheelchairLanes
    Indicates that a location, route, or facility includes designated lanes or pathways specifically designed for wheelchair use.
  • D. someRightOfWayUsedBy
    Indicates that a particular right of way is utilized or traversed by a specified user, route, or transport entity.
  • E. hasPedestrianAccessTo
    Indicates that a location or area can be reached or entered safely and directly by people on foot.
  • F. None of above.

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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc39c6ff0819081a07696f1c29990 completed March 7, 2026, 6:20 a.m.
PD Predicate disambiguation batch_69abbdb7719081909143efa8f48df4e4 completed March 7, 2026, 5:55 a.m.
Created at: March 4, 2026, 7:48 p.m.