Triple

T12568885
Position Surface form Disambiguated ID Type / Status
Subject Braga railway station E295545 entity
Predicate hasCommercialServices P105471 FINISHED
Object yes 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: yes | Statement: [Braga railway station, hasCommercialServices, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCommercialServices
Context triple: [Braga railway station, hasCommercialServices, yes]
  • A. hasCommercialFunction
    Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
  • B. hasCommercialField
    Indicates that one entity possesses or is associated with a commercial-related field, area, or domain in relation to another entity.
  • C. hasDirectServices
    Indicates that one entity provides services directly to another entity without intermediaries.
  • D. hasSupportService
    Indicates that one entity provides or is associated with a support-related service for another entity.
  • E. hasConstituentServicesIn
    Indicates that an entity provides constituent services within a specified geographic or jurisdictional area.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9550d84908190aea0f50055f6d92e completed April 10, 2026, 7:52 p.m.
PD Predicate disambiguation batch_69d95414692881909c52a1de7d224b44 completed April 10, 2026, 7:48 p.m.
PDg Predicate description generation batch_69d9550af6d48190a40e349ed0424be3 completed April 10, 2026, 7:52 p.m.
Created at: April 8, 2026, 11:50 p.m.