Triple

T14865989
Position Surface form Disambiguated ID Type / Status
Subject District XIV E349616 entity
Predicate neighboringDistrict P17964 FINISHED
Object District XIII E70143 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: District XIII | Statement: [District XIV, neighboringDistrict, District XIII]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: District XIII
Context triple: [District XIV, neighboringDistrict, District XIII]
  • A. District XIII chosen
    District XIII is a central district of Budapest known for its mix of residential neighborhoods, business centers, and the popular Margaret Island recreational area.
  • B. District VII
    District VII is an administrative district that neighbors District VI within its respective city or region.
  • C. District II
    District II is one of the geographic appellate divisions within the Oklahoma Court of Civil Appeals that hears and decides civil appeals from its assigned region of the state.
  • D. District II
    District II is one of the geographic appellate districts within the Wisconsin Court of Appeals that hears intermediate appeals from circuit courts in its assigned region of the state.
  • E. District V
    District V is a central district of Budapest, Hungary, known for its historic architecture, government buildings, and prominent shopping and tourist areas along the Danube River.
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5761c688190b4477cb081554b51 completed April 15, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e7fc904819094269b7c785ead69 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:55 a.m.