Triple

T1622241
Position Surface form Disambiguated ID Type / Status
Subject Leeds to Blackpool E35056 entity
Predicate connectsDestinationType P31057 FINISHED
Object major city 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: major city | Statement: [Leeds to Blackpool, connectsDestinationType, major city]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: connectsDestinationType
Context triple: [Leeds to Blackpool, connectsDestinationType, major city]
  • A. connectsTo
    Indicates a relationship where one entity is linked or joined to another, allowing interaction, communication, or transfer between them.
  • B. connectsDeviceType
    Indicates a relationship where one entity is associated with or linked to a specific type or category of device.
  • C. connectorType
    Indicates the specific kind or category of connection interface that links two entities.
  • D. servesDestinationCount
    Indicates the number of distinct destinations that an entity (such as a service, route, or provider) serves.
  • E. hasTeleconnectionsWith
    Indicates a relationship where changes or variations in one system, region, or variable are statistically linked to corresponding changes in another, often distant, system, region, or variable.
  • F. None of above. chosen

Provenance (4 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_69aaf4a0ef748190ae52b9656474c0ef completed March 6, 2026, 3:37 p.m.
PD Predicate disambiguation batch_69a907c731808190a1d998155041b3c1 completed March 5, 2026, 4:34 a.m.
PDg Predicate description generation batch_69a99ca48c888190876500df1a885c11 completed March 5, 2026, 3:09 p.m.
Created at: March 4, 2026, 7:28 p.m.