Triple

T3485098
Position Surface form Disambiguated ID Type / Status
Subject Dudley E73587 entity
Predicate locatedIn P40 FINISHED
Object Black Country E110670 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: Black Country | Statement: [Dudley, locatedIn, Black Country]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Black Country
Context triple: [Dudley, locatedIn, Black Country]
  • A. Black Country chosen
    The Black Country is an industrial region in the West Midlands of England historically known for coal mining, ironworking, and heavy manufacturing.
  • B. Black 47
    Black 47 is a 2018 Irish historical revenge thriller film set during the Great Famine, following a deserter from the British Army who returns home to find his family destroyed by starvation and injustice.
  • C. Up Country
    Up Country is a term commonly used to refer to the central highland region of Sri Lanka, known for its mountainous terrain, tea plantations, and cooler climate.
  • D. County of Kings
    County of Kings is the formal name for Brooklyn, a densely populated borough of New York City known for its cultural diversity and historic neighborhoods.
  • E. Poor Folk
    Poor Folk is Fyodor Dostoevsky’s debut epistolary novel that portrays the struggles and inner lives of impoverished clerks in 19th-century St. Petersburg.
  • 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_69ad85b3c9b08190857cae74c7f36da9 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb8f205c8190aa6f7484ebad14bb completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b368248f9c81908a1905a705e57c53 completed March 13, 2026, 1:28 a.m.
Created at: March 8, 2026, 3:17 p.m.