Triple

T11567462
Position Surface form Disambiguated ID Type / Status
Subject Oscar Martinez E274290 entity
Predicate coworker P398 FINISHED
Object Pam Beesly E223028 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: Pam Beesly | Statement: [Oscar Martinez, coworker, Pam Beesly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pam Beesly
Context triple: [Oscar Martinez, coworker, Pam Beesly]
  • A. Pam Beesly chosen
    Pam Beesly is a shy but witty receptionist-turned-office administrator and aspiring artist, best known as one of the central characters on the U.S. version of The Office.
  • B. Philip Schrute
    Philip Schrute is the infant son of Dwight Schrute in the television series "The Office."
  • C. Peggy Olson
    Peggy Olson is a central character in the television series "Mad Men," known for her rise from secretary to pioneering female copywriter in the 1960s advertising world.
  • D. Lisa Roberts
    Lisa Roberts is one of the children of Ralph J. Roberts, the American businessman best known as a co-founder of Comcast.
  • E. Mose Schrute
    Mose Schrute is a socially awkward, eccentric beet farmer and Dwight Schrute’s cousin who lives and works at Schrute Farms in the U.S. version of The Office.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd4305c8190ac5ff490b6b63e12 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e8c9a22c8190812c64b9f305ae99 completed April 21, 2026, 3:02 a.m.
Created at: April 8, 2026, 9:37 p.m.