Triple

T10082627
Position Surface form Disambiguated ID Type / Status
Subject Sömmerda district E213939 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object SÖM E459206 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: SÖM | Statement: [Sömmerda district, hasVehicleRegistrationCode, SÖM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SÖM
Context triple: [Sömmerda district, hasVehicleRegistrationCode, SÖM]
  • A. SÖM chosen
    SÖM is the vehicle registration code for the Sömmerda district in the German state of Thuringia.
  • B. Somosomo
    Somosomo is a coastal village on the Fijian island of Taveuni, known as a traditional center of chiefly authority and local administration.
  • C. сомони
    сомони — это денежная единица Таджикистана, названная в честь основателя таджикской государственности Исмоили Сомони.
  • D. SMO
    SMO is the IATA airport code for Santa Monica Airport, a general aviation facility located in Santa Monica, California.
  • E. SOU
    SOU is the three-letter National Rail station code for Southampton Central railway station in Hampshire, England.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd03482d481908b03d35dc2d16395 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b66b256c8190861066f7c19008d2 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.