Triple

T16338491
Position Surface form Disambiguated ID Type / Status
Subject Fremantle Dockers E396735 entity
Predicate shortName P43 FINISHED
Object Dockers E396735 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: Dockers | Statement: [Fremantle Dockers, shortName, Dockers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dockers
Context triple: [Fremantle Dockers, shortName, Dockers]
  • A. Dockers chosen
    Dockers is the common nickname for the Fremantle Dockers, an Australian Football League (AFL) club based in Fremantle, Western Australia.
  • B. Dockers
    Dockers is a popular global clothing brand best known for its casual khaki pants and business-casual apparel.
  • C. Skopeo
    Skopeo is a command-line utility for inspecting, copying, and managing container images across different container registries without requiring a local container engine.
  • D. Dockery
    Dockery is an English surname most notably associated with actress Michelle Dockery, known for her role in the television series "Downton Abbey."
  • E. Docker
    Docker is an open-source platform that uses containerization to package, distribute, and run applications consistently across different computing environments.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4e6338081908aa03ee3dcbe5f70 completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00261b31c08190908a72bff20871be completed May 10, 2026, 6:30 a.m.
Created at: April 10, 2026, 5:07 a.m.