Triple

T11111115
Position Surface form Disambiguated ID Type / Status
Subject WAW E262755 entity
Predicate hasPassengerTrafficRankInPoland P25678 FINISHED
Object 1 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: 1 | Statement: [WAW, hasPassengerTrafficRankInPoland, 1]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPassengerTrafficRankInPoland
Context triple: [WAW, hasPassengerTrafficRankInPoland, 1]
  • A. hasPassengerTrafficRank chosen
    Indicates the relative position or ranking of an entity based on the volume of passenger traffic it handles compared to others.
  • B. peakPassengerTrafficRank
    Indicates the relative position of an entity in an ordered list based on the amount of passenger traffic it experiences at its peak.
  • C. passengerTrafficRankInEurope
    Indicates the relative position of an entity in Europe based on the volume of passenger traffic it handles.
  • D. hasPassengerTrafficFrom
    Indicates that an entity receives or handles passenger traffic originating from another entity.
  • E. hasApproxAnnualPassengerUsageRank
    Indicates the approximate position or ranking of an entity based on its annual passenger usage compared to similar entities.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a6964508190b679303d3b3a4fd6 completed April 9, 2026, 12:24 p.m.
PD Predicate disambiguation batch_69d7441cf8188190b8095f622c923156 completed April 9, 2026, 6:15 a.m.
Created at: April 8, 2026, 9:27 p.m.