Triple

T4626112
Position Surface form Disambiguated ID Type / Status
Subject Seven Years in Tibet E101100 entity
Predicate starring P1507 FINISHED
Object Mako E237872 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: Mako | Statement: [Seven Years in Tibet, starring, Mako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mako
Context triple: [Seven Years in Tibet, starring, Mako]
  • A. Mako chosen
    Mako was a Japanese-American actor and voice actor known for his distinctive voice and roles in films like "Conan the Barbarian" and as the voice of Iroh in "Avatar: The Last Airbender."
  • B. Mako
    Mako is a Japanese imperial family member best known as Princess Mako of Akishino, the former princess who left royal status upon her marriage to a commoner.
  • C. Mako
    Mako is a high-speed steel roller coaster at SeaWorld Orlando themed around the ocean’s fastest shark.
  • D. Mako
    Mako is the nickname of Benjamin Mako Hill, a prominent free software activist, scholar, and developer involved with projects like Debian and Wikimedia.
  • E. Samu
    Samu is a given name, commonly used as a short form or variant of Samuel in various cultures.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a0a7b588190bc6552ee5babb198 completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaab30508190881828adab92ba22 completed March 21, 2026, 1:55 a.m.
Created at: March 20, 2026, 1:13 p.m.