Triple

T395950
Position Surface form Disambiguated ID Type / Status
Subject Godavari E8982 entity
Predicate hasTributary P415 FINISHED
Object Sabari E50418 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: Sabari | Statement: [Godavari, hasTributary, Sabari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabari
Context triple: [Godavari, hasTributary, Sabari]
  • A. 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.
  • B. Ponna
    Ponna was a prominent 10th-century Kannada poet of the Rashtrakuta court, renowned for his Jain devotional and classical literary works.
  • C. Sibi
    Sibi is a historic town and district in the Balochistan region of Pakistan, known for its hot climate and traditional annual cattle and horse fair.
  • D. Pranhita chosen
    Pranhita is a major river in central India that flows through the states of Maharashtra and Telangana before joining the Godavari River.
  • E. Sima Samar
    Sima Samar is an Afghan physician and human rights advocate renowned for her work promoting women's rights, education, and social justice in Afghanistan.
  • 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_69a2e7f55c60819097aff65ea2ca2832 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec792dd081909b6b18a854139f8c completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4254075388190af8fd09d037f427c completed March 1, 2026, 11:38 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.