Triple

T13154309
Position Surface form Disambiguated ID Type / Status
Subject Vaishali district E312543 entity
Predicate borders P224 FINISHED
Object Saran district E429903 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: Saran district | Statement: [Vaishali district, borders, Saran district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saran district
Context triple: [Vaishali district, borders, Saran district]
  • A. Saran district chosen
    Saran district is an administrative district in the Indian state of Bihar, known for its historical significance and location along the Ganges and Ghaghara rivers.
  • B. Sarine district
    Sarine district is an administrative district in the canton of Fribourg in western Switzerland, centered around the city of Fribourg and encompassing surrounding municipalities.
  • C. Andar District
    Andar District is an administrative district in southeastern Afghanistan known for its predominantly rural communities and history of conflict within Ghazni Province.
  • D. Maran District
    Maran District is an administrative district in the state of Pahang, Malaysia, known for its rural landscape and agricultural activities.
  • E. Bade District
    Bade District is an urban district in Taoyuan City, Taiwan, known for its residential communities and growing industrial and commercial development.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c06ccb881909390df18e1a6f7ed completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7941e0560819080eee43a9ed0e1bb completed May 3, 2026, 6:29 p.m.
Created at: April 9, 2026, 9:11 p.m.