Triple

T1320094
Position Surface form Disambiguated ID Type / Status
Subject Municipal Offices and Train Station Delft E28196 entity
Predicate client P27 FINISHED
Object NS Stations E28407 NE 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: NS Stations | Statement: [Municipal Offices and Train Station Delft, client, NS Stations]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NS Stations
Context triple: [Municipal Offices and Train Station Delft, client, NS Stations]
  • A. NS Stations chosen
    NS Stations is a Dutch company responsible for managing and developing railway stations and related facilities across the Netherlands.
  • B. Sol station
    Sol station is a major central railway and metro hub in Madrid, Spain, serving as a key interchange point for Cercanías commuter trains and multiple urban transit lines beneath Puerta del Sol.
  • C. Wawa station
    Wawa station is a commuter rail station in Wawa, Pennsylvania, serving as the terminus of SEPTA's Media/Wawa Line.
  • D. Wilson station
    Wilson station is a Toronto Transit Commission subway station on Line 1 Yonge–University in North York, serving the surrounding residential, commercial, and industrial areas.
  • E. Bethesda station
    Bethesda station is an underground Washington Metro station in Bethesda, Maryland, serving the Red Line and the surrounding downtown commercial district.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c179883c8190b68fbeebb9696982 completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbaf6a6d08190b8a30c2c64f15f59 completed March 7, 2026, 11:55 p.m.
Created at: March 1, 2026, 7:55 p.m.