Triple

T9082471
Position Surface form Disambiguated ID Type / Status
Subject Irkutsk International Airport E217667 entity
Predicate cityServed P82 FINISHED
Object Irkutsk E306994 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: Irkutsk | Statement: [Irkutsk International Airport, cityServed, Irkutsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irkutsk
Context triple: [Irkutsk International Airport, cityServed, Irkutsk]
  • A. Irkutsk chosen
    Irkutsk is a major city in southeastern Siberia, Russia, historically significant as a political and administrative center and a key hub during the Russian Civil War.
  • B. Krasnoyarsk
    Krasnoyarsk is a large industrial and cultural city in central Russia, situated on the Yenisei River and known as one of the key urban centers of Siberia.
  • C. Tobolsk
    Tobolsk is a historic Siberian town in Russia known for its Kremlin and as a place of exile and imprisonment during the late imperial period.
  • D. Omsk
    Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
  • E. Yakutsk
    Yakutsk is a major city in northeastern Siberia, Russia, known as one of the coldest large cities in the world and a key administrative and cultural center of the Sakha Republic.
  • 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_69ca83d7a0388190ba1af89ed7ba36f9 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc960a2760819084aab611eb1c43a9 completed April 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69d152541308819098cdca4f3ba9011d completed April 4, 2026, 6:03 p.m.
Created at: March 30, 2026, 7:13 p.m.