Triple

T11992111
Position Surface form Disambiguated ID Type / Status
Subject Alex Rodríguez E285431 entity
Predicate notableWork P4 FINISHED
Object The 33 E502217 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: The 33 | Statement: [Alex Rodríguez, notableWork, The 33]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The 33
Context triple: [Alex Rodríguez, notableWork, The 33]
  • A. The 33 chosen
    The 33 is a 2015 drama film that recounts the true story of the 2010 Chilean mining disaster and the rescue of 33 trapped miners.
  • B. The 305
    The 305 is a nickname commonly used to refer to Miami, Florida, derived from its original area code.
  • C. The 355
    The 355 is a 2022 female-led espionage action thriller film about an international team of spies who unite to stop a global threat.
  • D. 13 Going on 30
    13 Going on 30 is a 2004 romantic comedy fantasy film about a 13-year-old girl who magically wakes up in her 30-year-old body and must navigate adulthood, starring Jennifer Garner.
  • E. Time for Three
    Time for Three is a genre-blending string trio known for fusing classical music with jazz, pop, and other contemporary styles in highly energetic performances.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903b11ac481909866b611380792e7 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4726696dc8190bf2a7aa43cb08b19 completed May 1, 2026, 9:29 a.m.
Created at: April 8, 2026, 9:46 p.m.