Triple

T16410840
Position Surface form Disambiguated ID Type / Status
Subject Esslingen am Neckar E398557 entity
Predicate twinTown P1072 FINISHED
Object Eger, Hungary E338315 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: Eger, Hungary | Statement: [Esslingen am Neckar, twinTown, Eger, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eger, Hungary
Context triple: [Esslingen am Neckar, twinTown, Eger, Hungary]
  • A. Eger chosen
    Eger is a historic city in northern Hungary known for its baroque architecture, castle, and wine culture.
  • B. Eger
    Eger is the former German name for the Czech town of Cheb, a historic settlement near the German border in western Bohemia.
  • C. Kaposvár, Hungary
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • D. Kisvárda, Hungary
    Kisvárda is a small town in northeastern Hungary known for its historic castle, thermal baths, and role as a regional cultural and economic center.
  • E. Budaörs, Hungary
    Budaörs is a suburban town just west of Budapest in Hungary, known for its rapid post-communist development, commercial centers, and role as a key transport hub near the capital.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328731a408190b38dcab0b7bb65ff completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c66d41481909340f247f6e5393f completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:09 a.m.