Triple

T11529084
Position Surface form Disambiguated ID Type / Status
Subject Sibiu County E273370 entity
Predicate traversedByRiver P165 FINISHED
Object Cibin River E401696 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: Cibin River | Statement: [Sibiu County, traversedByRiver, Cibin River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cibin River
Context triple: [Sibiu County, traversedByRiver, Cibin River]
  • A. Cibin River chosen
    The Cibin River is a significant river in central Romania that flows through Sibiu County and the city of Sibiu before joining the Olt River.
  • B. Jintsu River
    Jintsu River is a river in Japan known for flowing through Toyama Prefecture and lending its name to the Imperial Japanese Navy light cruiser IJN Jintsu.
  • C. Bunsuru River
    The Bunsuru River is a tributary watercourse in northwestern Nigeria that feeds into the larger Sokoto River system.
  • D. Ngashih River
    Ngashih River is a tributary watercourse in northeastern India that feeds into the larger Tlawng River system.
  • E. Kerinchi River
    Kerinchi River is a smaller waterway in the Klang Valley region of Malaysia that feeds into the larger Klang River system.
  • 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_69d6aae3fbec8190a14632a5df2538b6 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d883972b10819093bd09cf8406671c completed April 10, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbb445a48190ba3dafb1f076ac83 completed May 10, 2026, 1:13 a.m.
Created at: April 8, 2026, 9:37 p.m.