Triple

T13628826
Position Surface form Disambiguated ID Type / Status
Subject Liz Gorinsky E325658 entity
Predicate workedFor P1910 FINISHED
Object Tor Books E159906 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: Tor Books | Statement: [Liz Gorinsky, workedFor, Tor Books]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tor Books
Context triple: [Liz Gorinsky, workedFor, Tor Books]
  • A. Tor Books chosen
    Tor Books is a major American science fiction and fantasy publishing imprint known for releasing influential genre novels and series.
  • B. Titan Books
    Titan Books is a British publishing house known for releasing tie-in fiction, art books, and non-fiction works based on popular film, television, and comic franchises.
  • C. Forge Books
    Forge Books is an American publishing imprint known for releasing a wide range of commercial fiction, including thrillers, mysteries, and general-interest novels, under the broader Tor/Forge publishing group.
  • D. Pocket Books
    Pocket Books is a long-running American mass-market paperback publisher known for popular fiction and non-fiction titles, operating as an imprint of Simon & Schuster.
  • E. Fox Books
    Fox Books is a large, corporate bookstore chain featured in the film "You've Got Mail," representing the big-box competitor to independent bookshops.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbbe9d803481908101def32817b0eb completed April 12, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78aeb591481909d39675a543a8b51 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:51 p.m.