Triple

T12869138
Position Surface form Disambiguated ID Type / Status
Subject Hotel Mumbai E307801 entity
Predicate director P255 FINISHED
Object Anthony Maras E580889 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: Anthony Maras | Statement: [Hotel Mumbai, director, Anthony Maras]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anthony Maras
Context triple: [Hotel Mumbai, director, Anthony Maras]
  • A. Anthony Maras chosen
    Anthony Maras is an Australian film director and screenwriter best known for the critically acclaimed thriller "Hotel Mumbai."
  • B. Anthony Maraschi
    Anthony Maraschi was a 19th-century Italian Jesuit priest who played a key role in establishing Catholic education in California, most notably by founding the institution that became the University of San Francisco.
  • C. Anthony Marinelli
    Anthony Marinelli is an American composer and musician best known for his film scores and extensive work in Hollywood soundtracks.
  • D. Anthony Marentino
    Anthony Marentino is a flamboyant, quick-witted wedding planner and stylist best known as Charlotte York’s close friend and eventual husband on the television series "Sex and the City."
  • E. Peter Maranian
    Peter Maranian is the husband of Pulitzer Prize–winning American columnist and author Ellen Goodman.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9708f510c8190b4c64dc340420e85 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af533d188190b9c816cdc892fe99 completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:38 p.m.