Triple

T4685124
Position Surface form Disambiguated ID Type / Status
Subject Bellshill E103901 entity
Predicate hasPostcodeArea P920 FINISHED
Object ML E137195 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: ML | Statement: [Bellshill, hasPostcodeArea, ML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ML
Context triple: [Bellshill, hasPostcodeArea, ML]
  • A. ML
    ML is a statically typed functional programming language developed at the University of Edinburgh, known for pioneering features like type inference, pattern matching, and modules that strongly influenced later languages such as Elm, Haskell, and OCaml.
  • B. ML chosen
    ML is the postcode area in central Scotland that covers Motherwell and surrounding towns.
  • C. ML
    ML is a post-nominal honorific indicating a recipient of Papua New Guinea’s Order of Logohu, a national order of merit.
  • D. MS in Machine Learning
    MS in Machine Learning is a specialized graduate program at Carnegie Mellon University focused on advanced theory and applications of machine learning and statistical methods for building intelligent systems.
  • E. LFD
    LFD is the National Rail station code for Lingfield railway station in Surrey, 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_69bd43debbf08190b4bc372e286ec234 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63829b048190a2044de900ef7a69 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03b3b0208190bb307cdd53f44306 completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:16 p.m.