Triple

T4215863
Position Surface form Disambiguated ID Type / Status
Subject Nita Naldi E94212 entity
Predicate coStarredWith P14987 FINISHED
Object Antonio Moreno E306992 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: Antonio Moreno | Statement: [Nita Naldi, coStarredWith, Antonio Moreno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antonio Moreno
Context triple: [Nita Naldi, coStarredWith, Antonio Moreno]
  • A. Antonio Moreno chosen
    Antonio Moreno was a Spanish-born American actor prominent in early Hollywood cinema, known for his roles in silent films and later sound productions.
  • B. Antonio Reynoso
    Antonio Reynoso is an American politician and community advocate who serves as the Borough President of Brooklyn, New York City.
  • C. Antonio Rivera Rodríguez
    Antonio Rivera Rodríguez was a notable Puerto Rican figure after whom the main airport on the island of Vieques is named.
  • D. Lou Antonio
    Lou Antonio is an American actor and television director known for his work in film and TV from the 1960s onward, including roles in socially conscious dramas and popular series.
  • E. Alejandro Moreno
    Alejandro Moreno is a Venezuelan former professional soccer forward known for his successful Major League Soccer career, including key contributions to multiple MLS Cup–winning teams.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34bea284081909beaded9873f0852 completed March 12, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67ac56548190a2d52b055cb48e8e completed March 21, 2026, 9:41 a.m.
Created at: March 12, 2026, 11:04 p.m.