Triple

T1738103
Position Surface form Disambiguated ID Type / Status
Subject RDS E37965 entity
Predicate hasSisterChannel P6991 FINISHED
Object RDS Info 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 Info | Statement: [RDS, hasSisterChannel, RDS Info]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RDS Info
Context triple: [RDS, hasSisterChannel, RDS Info]
  • A. RDS chosen
    RDS is a Canadian French-language sports television network that broadcasts a wide range of professional and amateur sporting events.
  • B. 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.
  • C. DB
    DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
  • D. DSN
    DSN is the acronym for NASA’s Deep Space Network, a global system of large radio antennas used to communicate with and track interplanetary spacecraft and distant space missions.
  • E. MariaDB
    MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
  • 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_69a8861cc6ac8190ac0b2e31ccf62851 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c35aec8190b5c19ace5524173f completed March 6, 2026, 5:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8b03303c8190a301dca327bf9f47 completed March 8, 2026, 2:43 p.m.
Created at: March 4, 2026, 7:30 p.m.