Triple

T3550130
Position Surface form Disambiguated ID Type / Status
Subject America Ferrera E75090 entity
Predicate givenName P17 FINISHED
Object America E90426 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: America | Statement: [America Ferrera, givenName, America]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: America
Context triple: [America Ferrera, givenName, America]
  • A. America
    "America" is a lively, satirical musical number from *West Side Story* that contrasts the promises and prejudices of life in the United States as debated by Puerto Rican immigrants.
  • B. America
    "America" is a seminal and politically charged Judge Dredd storyline that explores themes of democracy, authoritarianism, and personal freedom within the dystopian world of Mega-City One.
  • C. America chosen
    America is the landmass in the Western Hemisphere comprising the continents of North and South America, widely recognized for its vast geographic, cultural, and political diversity.
  • D. America
    America was the Command and Service Module spacecraft used on NASA’s Apollo 17 mission, the final crewed lunar landing of the Apollo program.
  • E. Amerika
    Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
  • 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_69ad85d33c6c819081d5ac1df13b5680 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbfd38c8c8190a4591689ad57c998 completed March 8, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51203d6148190a9946a3f274e21a5 completed March 14, 2026, 7:45 a.m.
Created at: March 8, 2026, 3:20 p.m.