Triple

T3536274
Position Surface form Disambiguated ID Type / Status
Subject Jennifer Aniston as Dr. Julia Harris E74779 entity
Predicate countryOfFilmProduction P15638 FINISHED
Object UnitedStates E14 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: UnitedStates | Statement: [Jennifer Aniston as Dr. Julia Harris, countryOfFilmProduction, UnitedStates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UnitedStates
Context triple: [Jennifer Aniston as Dr. Julia Harris, countryOfFilmProduction, UnitedStates]
  • A. Usan
    Usan is a small coastal village in Angus, Scotland, known for its fishing heritage and scenic North Sea shoreline.
  • B. United States of America chosen
    The United States of America is a large federal republic in North America known for its global political, economic, military, and cultural influence.
  • C. Us
    Us is a 2019 horror film written and directed by Jordan Peele that explores themes of identity and duality through a family's terrifying encounter with their doppelgängers.
  • D. Us
    "Us" is a soulful pop ballad by British singer-songwriter James Bay that explores themes of hope, connection, and emotional vulnerability.
  • E. US
    US is the IATA airline designator code assigned to the former American airline US Airways.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbcc7b92481908d2d99948780f4d0 completed March 8, 2026, 6:15 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.