Triple

T12635710
Position Surface form Disambiguated ID Type / Status
Subject Beijing West railway station E301757 entity
Predicate designedPassengerCapacityPerDay P30663 FINISHED
Object 300000 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: 300000 | Statement: [Beijing West railway station, designedPassengerCapacityPerDay, 300000]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: designedPassengerCapacityPerDay
Context triple: [Beijing West railway station, designedPassengerCapacityPerDay, 300000]
  • A. maximumPassengerCapacity
    Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
  • B. hasDailyPassengerTraffic chosen
    Indicates the number of passengers that regularly use or pass through something (such as a station or route) each day.
  • C. transportCapacity
    Indicates the maximum quantity of people, goods, or materials that can be transported by an entity or system within a given operation or time frame.
  • D. designedCargoCapacity
    Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
  • E. passengerCapacityCategory
    Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961ae493481908f82e0d05dce20bd completed April 10, 2026, 8:46 p.m.
PD Predicate disambiguation batch_69d960b47130819097e1162ed4fc993a completed April 10, 2026, 8:42 p.m.
Created at: April 9, 2026, 5:16 p.m.