Triple

T11258382
Position Surface form Disambiguated ID Type / Status
Subject Gautrain E266498 entity
Predicate connectsTo P845 FINISHED
Object Hatfield E211873 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: Hatfield | Statement: [Gautrain, connectsTo, Hatfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hatfield
Context triple: [Gautrain, connectsTo, Hatfield]
  • A. Hatfield
    Hatfield is a surname most prominently associated with Mark O. Hatfield, a long-serving U.S. senator and governor from Oregon.
  • B. Hatfield chosen
    Hatfield is a historic town in Hertfordshire, England, known for Hatfield House and its strong connections to Tudor and Stuart royal history.
  • C. Carlisle
    Carlisle is a historic borough in south-central Pennsylvania known for its military education institutions, colonial heritage, and role in the American Revolutionary era.
  • D. Carlisle
    Carlisle is a historic cathedral city and county town of Cumbria in North West England, near the Scottish border.
  • E. Carlisle
    Carlisle is a small city located in central Iowa, United States, known for its close-knit community and proximity to the Des Moines metropolitan area.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e936cb048190b4d6fb2851ef8932 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ccada158819080e49833e09f84a0 completed April 19, 2026, 12:38 p.m.
Created at: April 8, 2026, 9:31 p.m.