Triple

T15729864
Position Surface form Disambiguated ID Type / Status
Subject Masako E381313 entity
Predicate givenName P17 FINISHED
Object Masako E381313 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: Masako | Statement: [Masako, givenName, Masako]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masako
Context triple: [Masako, givenName, Masako]
  • A. Masako chosen
    Masako is the Empress of Japan, a former diplomat and Harvard-educated member of the Imperial House known for her international background and public role.
  • B. Misako
    Misako is a key character in the Ninjago universe, known as an archaeologist and historian who is the mother of Lloyd Garmadon and the wife of Garmadon.
  • C. Sachiko
    Sachiko is a Japanese feminine given name that can be written with various kanji combinations, often conveying meanings related to happiness or child.
  • D. Kazuko
    Kazuko is a Japanese feminine given name commonly borne by women, including members of the imperial family.
  • E. Yuriko
    Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fb61cb881908b158609c1ccfa1e completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa9341a0c81909057dc338f218b85 completed May 9, 2026, 9:37 p.m.
Created at: April 10, 2026, 4:46 a.m.