Triple

T18224764
Position Surface form Disambiguated ID Type / Status
Subject Tani Tateki E436394 entity
Predicate familyName P18 FINISHED
Object Tani NE NERFINISHED

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: Tani | Statement: [Tani Tateki, familyName, Tani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tani
Context triple: [Tani Tateki, familyName, Tani]
  • A. Tani
    Tani is a group of closely related Tibeto-Burman languages spoken primarily in the northeastern Indian states of Arunachal Pradesh and Assam.
  • B. Tani
    Tani is a Pashtun tribal group primarily associated with Afghanistan’s Khost region.
  • C. Tani Tateki chosen
    Tani Tateki was a Japanese samurai and military commander of the Meiji era who played a key role in government forces during the Satsuma Rebellion.
  • D. Yulu
    Yulu is a Central Sudanic language spoken by the Yulu people primarily in parts of South Sudan and the Central African Republic.
  • E. Hani
    The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9103a8081908bbb0836fef10efd completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e47e5e8c819095454b6557a5d5a5 completed April 19, 2026, 2:19 p.m.
Created at: April 10, 2026, 10:32 a.m.