Triple

T3048880
Position Surface form Disambiguated ID Type / Status
Subject Saga E83519 entity
Predicate knownFor P22 FINISHED
Object Saga ware E83519 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: Saga ware | Statement: [Saga, knownFor, Saga ware]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saga ware
Context triple: [Saga, knownFor, Saga ware]
  • A. Saga
    Saga is a critically acclaimed science fiction/fantasy comic series by Brian K. Vaughan and Fiona Staples, renowned for its genre-blending storytelling, mature themes, and distinctive artwork.
  • B. Saga chosen
    Saga is a small coastal city in northern Kyushu, Japan, known as the capital of Saga Prefecture and for its historic sites and traditional ceramics.
  • C. Starbrand
    Starbrand is a powerful cosmic superhero in Marvel Comics who wields an energy-based mark granting immense abilities and has been associated with teams like the Avengers.
  • D. Oreshura
    Oreshura is a Japanese romantic comedy light novel and anime series that follows a high school boy roped into a fake relationship with a popular girl to fend off unwanted romantic attention.
  • E. Shinsen
    Shinsen is a neighborhood in Tokyo’s Shibuya ward known for its residential streets, local eateries, and proximity to the bustling Shibuya Station area.
  • 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_69ad8b24924c8190a9bb6f61d519e4ae completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9baed3848190a8351d9c8c4edc79 completed March 8, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1eef7d1e081908535b7d972a147eb completed March 11, 2026, 10:38 p.m.
Created at: March 8, 2026, 3:01 p.m.