Triple

T4272595
Position Surface form Disambiguated ID Type / Status
Subject Love Me Tonight E96973 entity
Predicate screenwriter P2831 FINISHED
Object Samuel Hoffenstein E240474 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: Samuel Hoffenstein | Statement: [Love Me Tonight, screenwriter, Samuel Hoffenstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samuel Hoffenstein
Context triple: [Love Me Tonight, screenwriter, Samuel Hoffenstein]
  • A. Samuel Hoffenstein chosen
    Samuel Hoffenstein was an American screenwriter and poet best known for his witty, sophisticated scripts in Hollywood films of the 1930s and 1940s.
  • B. Yehuda Hoffman
    Yehuda Hoffman is an astrophysicist known for his work in cosmology and large-scale structure, including helping identify and characterize the Laniakea Supercluster.
  • C. Louis Finkelstein
    Louis Finkelstein was a prominent American Conservative rabbi and scholar who served as a long-time leader and chancellor of the Jewish Theological Seminary of America.
  • D. Michael Waldstein
    Michael Waldstein is a Catholic theologian and scholar best known for his authoritative English translation and commentary on Pope John Paul II’s Theology of the Body.
  • E. Isaac Ehrlich
    Isaac Ehrlich is an economist known for his work on the economic analysis of crime, deterrence, and the death penalty.
  • 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ffe44508190875d734eb18dfb87 completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf28ea49588190bf1bc4cb3ca4dcee completed March 21, 2026, 11:25 p.m.
Created at: March 12, 2026, 11:07 p.m.