Triple

T8516333
Position Surface form Disambiguated ID Type / Status
Subject Robert Patrick E201580 entity
Predicate portrayed P1668 FINISHED
Object T-1000 E226450 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: T-1000 | Statement: [Robert Patrick, portrayed, T-1000]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: T-1000
Context triple: [Robert Patrick, portrayed, T-1000]
  • A. T-1000 chosen
    The T-1000 is a shape-shifting, liquid-metal assassin android and primary antagonist in the film "Terminator 2: Judgment Day."
  • B. T-800
    The T-800 is a model of cybernetic assassin and soldier from the Terminator franchise, most famously portrayed by Arnold Schwarzenegger as a time-traveling killer robot with a human appearance.
  • C. T-X
    The T-X is an advanced, shape-shifting Terminator model from the Terminator franchise, designed as a highly lethal, next-generation assassin android.
  • D. John T. Connor
    John T. Connor was an American businessman and public official who served as U.S. Secretary of Commerce under President Lyndon B. Johnson.
  • E. Agent Smith
    Agent Smith is the primary antagonist of The Matrix franchise, a relentless, self-aware computer program that seeks to eradicate humanity and escape the control of the Matrix.
  • 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe62550908190af882019d68a904a completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e65419481909e787066fd069565 completed April 2, 2026, 11:09 a.m.
Created at: March 30, 2026, 6:15 p.m.