Triple

T22458513
Position Surface form Disambiguated ID Type / Status
Subject Beary E555173 entity
Predicate alternativeName P39 FINISHED
Object Byari 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: Byari | Statement: [Beary, alternativeName, Byari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Byari
Context triple: [Beary, alternativeName, Byari]
  • A. Byari chosen
    Byari is a Dravidian language spoken primarily by the Beary Muslim community in coastal Karnataka, India.
  • B. Bolari
    Bolari is a town and administrative ward located within Gombe State in northeastern Nigeria.
  • C. Barshaini
    Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
  • D. Barabai
    Barabai is a town and administrative center in Hulu Sungai Tengah Regency on the island of Borneo in Indonesia’s South Kalimantan province.
  • E. Bariadi
    Bariadi is a town in northern Tanzania that serves as an important local administrative and commercial center.
  • 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_69e11e51fdec8190adfdf9f8a6362221 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b7d00208190955a70e2c22d25a4 completed April 29, 2026, 1:14 a.m.
Created at: April 16, 2026, 8:48 p.m.