Triple

T5825003
Position Surface form Disambiguated ID Type / Status
Subject Bishop of Tambov E129200 entity
Predicate seat P75 FINISHED
Object Tambov E514739 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: Tambov | Statement: [Bishop of Tambov, seat, Tambov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tambov
Context triple: [Bishop of Tambov, seat, Tambov]
  • A. Tambov chosen
    Tambov is a city in western Russia known as an administrative, cultural, and industrial center of the Tambov Oblast.
  • B. Oryol
    Oryol was a notable warship of the Imperial Russian Navy, recognized for its role in Russia’s early modern naval history.
  • C. Belgorod
    Belgorod is a city in western Russia near the Ukrainian border, historically significant as a strategic site of major World War II battles and offensives.
  • D. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • E. Ryazan
    Ryazan is a historic city in western Russia known for its medieval kremlin, role as a regional cultural and economic center, and legacy as one of the country’s oldest urban settlements.
  • 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_69c00849d55481908b4f9f5543e0bf6d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0341a85988190be988f1c0722da66 completed March 22, 2026, 6:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c669d13b788190a6568d2d080ebdc6 completed March 27, 2026, 11:28 a.m.
Created at: March 22, 2026, 3:53 p.m.