Triple

T5420637
Position Surface form Disambiguated ID Type / Status
Subject Dr. Seuss E121238 entity
Predicate employer P7 FINISHED
Object PM magazine E403488 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: PM magazine | Statement: [Dr. Seuss, employer, PM magazine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PM magazine
Context triple: [Dr. Seuss, employer, PM magazine]
  • A. PM Magazine chosen
    PM Magazine was a popular American syndicated television news and entertainment magazine show that aired locally produced segments across numerous stations in the late 1970s and 1980s.
  • B. IPC Magazines
    IPC Magazines was a major British publishing company known for producing popular comics and magazines, including the early home of the Judge Dredd character.
  • C. The Magazine of Magazines
    The Magazine of Magazines was an 18th-century British periodical that compiled and reprinted notable literary and political works for a broad reading public.
  • D. Press Gazette
    Press Gazette is a UK-based media industry publication that covers journalism and the news business, including reporting on and organizing major press awards.
  • E. People (magazine)
    People is a popular American weekly magazine best known for its celebrity news, human-interest stories, and annual features like "Sexiest Man Alive."
  • 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_69bd463b58d88190b258261573de9e91 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87eac41481908a4982db5d119edd completed March 20, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3ab4d32c8190958daefa8061a7f9 completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:06 p.m.