Triple

T2245205
Position Surface form Disambiguated ID Type / Status
Subject Ilsa Lund E49486 entity
Predicate spouse P13 FINISHED
Object Victor Laszlo E48994 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: Victor Laszlo | Statement: [Ilsa Lund, spouse, Victor Laszlo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor Laszlo
Context triple: [Ilsa Lund, spouse, Victor Laszlo]
  • A. Victor Laszlo chosen
    Victor Laszlo is a heroic resistance leader and freedom fighter in the classic film "Casablanca," known for his unwavering courage and moral integrity.
  • B. Felix Krull
    Felix Krull is the charming, quick-witted con artist and social climber who narrates Thomas Mann’s picaresque novel "The Confessions of Felix Krull."
  • C. Count László de Almásy
    Count László de Almásy is a mysterious, badly burned Hungarian cartographer and desert explorer whose fragmented memories and tragic love affair drive the narrative of Michael Ondaatje’s novel and its film adaptation, The English Patient.
  • D. Andrew Laszlo
    Andrew Laszlo was a Hungarian-American cinematographer known for his work on films such as "The Warriors," "First Blood," and "Streets of Fire."
  • E. Ernest Laszlo
    Ernest Laszlo was a Hungarian-American cinematographer renowned for his work on numerous classic Hollywood films and for winning an Academy Award for Best Cinematography.
  • 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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0e8d5648190915ff689c7ca42bc completed March 7, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b1284d0819093b041ede90d4c53 completed March 9, 2026, 6:39 a.m.
Created at: March 4, 2026, 7:47 p.m.