Triple

T13258545
Position Surface form Disambiguated ID Type / Status
Subject Rob Thomas E315726 entity
Predicate writerOf P2831 FINISHED
Object Veronica Mars (2014 film) E81053 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: Veronica Mars (2014 film) | Statement: [Rob Thomas, writerOf, Veronica Mars (2014 film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Veronica Mars (2014 film)
Context triple: [Rob Thomas, writerOf, Veronica Mars (2014 film)]
  • A. Veronica Mars chosen
    Veronica Mars is a neo-noir mystery television series (later continued in film and revival form) centered on a sharp-witted teenage private investigator navigating crime and corruption in the fictional town of Neptune, California.
  • B. Leo D’Amato on Veronica Mars
    Leo D’Amato is a kind-hearted Neptune police officer and occasional love interest of Veronica Mars in the television series "Veronica Mars."
  • C. Veronica
    Veronica is a central character from the Archie Comics series, known as the wealthy, stylish, and often temperamental love interest of Archie Andrews.
  • D. Veronica
    Veronica is the given first name of the American actress and comedian Patsy Kelly.
  • E. Veronica
    Veronica is a fictional character known as a relative of Tiffany Maxwell in the film "Silver Linings Playbook."
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f778088819082b8a596c04bfe02 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716c90c5c8190a6de94b92db12210 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:25 p.m.