Triple

T924815
Position Surface form Disambiguated ID Type / Status
Subject Alcinous E19959 entity
Predicate associatedWith P37 FINISHED
Object Nausicaa E18792 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: Nausicaa | Statement: [Alcinous, associatedWith, Nausicaa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nausicaa
Context triple: [Alcinous, associatedWith, Nausicaa]
  • A. Nausicaa chosen
    Nausicaa is a Phaeacian princess in Greek mythology who aids the shipwrecked Odysseus in Homer’s Odyssey, embodying hospitality, innocence, and budding romantic possibility.
  • B. Tora
    Tora is a popular nickname for the Hanshin Tigers, a professional Japanese baseball team based in the Kansai region.
  • C. Shenwa
    Shenwa is a Zenati Berber language spoken by a small community in the Chenoua (Shenwa) region of northern Algeria.
  • D. Kaiyukan
    Kaiyukan is a large, world-renowned public aquarium in Osaka, Japan, famous for its massive central tank and immersive marine life exhibits.
  • E. Ahirani
    Ahirani is an Indo-Aryan dialect spoken primarily in the Khandesh region of Maharashtra, India, closely related to Marathi but with distinct phonological and lexical features.
  • 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_69a493a099788190a696d9d8408cbaf4 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b32ad9f88190b7d477d0a9a9dbc8 completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a826d8f9408190aa286bb809507797 completed March 4, 2026, 12:34 p.m.
Created at: March 1, 2026, 7:40 p.m.