Triple

T3422800
Position Surface form Disambiguated ID Type / Status
Subject Little Women (1933 film) E72151 entity
Predicate starring P1507 FINISHED
Object Paul Lukas E224153 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: Paul Lukas | Statement: [Little Women (1933 film), starring, Paul Lukas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Lukas
Context triple: [Little Women (1933 film), starring, Paul Lukas]
  • A. Paul Lukas chosen
    Paul Lukas was a Hungarian-American actor known for his distinguished stage and film career, including an Academy Award-winning performance in "Watch on the Rhine."
  • B. Joseph Markovitch
    Joseph Markovitch was the father of French photographer and painter Dora Maar, a key figure in the Surrealist movement and companion of Pablo Picasso.
  • C. Paul Seydor
    Paul Seydor is a film editor and scholar best known for his work on Sam Peckinpah’s films and his writings on American cinema.
  • D. Walter Abel
    Walter Abel was an American stage, film, and television character actor active from the silent era through the mid-20th century.
  • E. Peter Hermann
    Peter Hermann is an American actor and producer best known for his roles on television series such as "Law & Order: Special Victims Unit" and "Younger."
  • 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_69ad85ad38e48190b7660c5118a35289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb95223e081908b2954769d2f46c8 completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b35472881c8190baf90b91daa924ec completed March 13, 2026, 12:04 a.m.
Created at: March 8, 2026, 3:15 p.m.