Triple

T9967632
Position Surface form Disambiguated ID Type / Status
Subject Morpheus E195724 entity
Predicate enemyOf P437 FINISHED
Object the Machines E832014 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 Machines | Statement: [Morpheus, enemyOf, the Machines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: the Machines
Context triple: [Morpheus, enemyOf, the Machines]
  • A. the Machines chosen
    The Machines are the highly advanced artificial intelligences that dominate and enslave humanity in the Matrix film series.
  • B. The Machine
    The Machine is the nickname of Albert Pujols, a Dominican-American former Major League Baseball first baseman renowned for his remarkably consistent and powerful hitting.
  • C. The Machine
    The Machine is a powerful, clandestine artificial superintelligence from the TV series "Person of Interest" that predicts violent crimes by analyzing global surveillance data.
  • D. La Máquina
    La Máquina is the popular nickname of Mexican football club Cruz Azul, highlighting its reputation as a powerful, relentless team.
  • E. Man and Machine
    "Man and Machine" is a key chapter in Peter Thiel’s book "Zero to One" that explores how humans and computers can best complement each other in creating innovative, future-defining technologies.
  • 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_69ca82ebd1288190912f9e4482d1fa35 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb71f9d7c8190ac02c53052c1c6ad completed April 2, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257c002cc8190becc9730b2c01782 completed April 5, 2026, 12:38 p.m.
Created at: March 30, 2026, 8:47 p.m.