Triple

T8514820
Position Surface form Disambiguated ID Type / Status
Subject 1999 NHL All-Star Game E201545 entity
Predicate televisionNetworkCanada P833 FINISHED
Object RDS E37965 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: RDS | Statement: [1999 NHL All-Star Game, televisionNetworkCanada, RDS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RDS
Context triple: [1999 NHL All-Star Game, televisionNetworkCanada, RDS]
  • A. RDS
    RDS is a Microsoft Windows Server role that enables users to remotely access desktops and applications hosted on centralized servers.
  • B. RDS chosen
    RDS is a Canadian French-language sports television network that broadcasts a wide range of professional and amateur sporting events.
  • C. RDS2
    RDS2 is a Swiss French-language television channel that serves as a secondary sports-focused outlet to the main Réseau des sports (RDS) network.
  • D. Amazon RDS
    Amazon RDS is a managed relational database service by Amazon Web Services that simplifies setup, operation, and scaling of databases in the cloud.
  • E. ApsaraDB for RDS
    ApsaraDB for RDS is Alibaba Cloud’s managed relational database service that provides scalable, high-availability SQL databases with automated management and security features.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60e12848190a4a3dfa457aef275 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e56ef088190b4f938486bbb7962 completed April 2, 2026, 11:09 a.m.
Created at: March 30, 2026, 6:15 p.m.