Triple

T22241080
Position Surface form Disambiguated ID Type / Status
Subject Rushani E549723 entity
Predicate alternateName P39 FINISHED
Object Rushanī 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: Rushanī | Statement: [Rushani, alternateName, Rushanī]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rushanī
Context triple: [Rushani, alternateName, Rushanī]
  • A. Rushan
    Rushan is a county-level coastal city in eastern Shandong Province, China, known for its fishing industry, beaches, and marine-based economy.
  • B. Rushani chosen
    Rushani is an Eastern Iranian language spoken primarily in the Rushan region of Tajikistan and neighboring areas.
  • C. Razihi
    Razihi is a highly divergent Arabic-related language spoken by a small community in the mountainous Jabal Razih region of northwestern Yemen.
  • D. 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.
  • E. Makhshirin
    Makhshirin is a tractate of the Mishnah in Seder Tohorot that deals with the liquids and conditions that render foods susceptible to ritual impurity.
  • 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_69e11e41d9408190bd770cf282e22753 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f132140ed481909ab0d4022756a4ba completed April 28, 2026, 10:17 p.m.
Created at: April 16, 2026, 8:38 p.m.