Triple

T15465046
Position Surface form Disambiguated ID Type / Status
Subject DfT category C2 E372009 entity
Predicate distinguishedFrom P1612 FINISHED
Object DfT category F1 E990091 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: DfT category F1 | Statement: [DfT category C2, distinguishedFrom, DfT category F1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DfT category F1
Context triple: [DfT category C2, distinguishedFrom, DfT category F1]
  • A. Department for Transport category F1 chosen
    Department for Transport category F1 is a UK railway station classification denoting a very small, typically unstaffed local station with low passenger usage and basic facilities.
  • B. DfT category F2
    DfT category F2 is a UK Department for Transport classification for very small, lightly used railway stations with minimal facilities.
  • C. DfT category C1
    DfT category C1 is a UK Department for Transport classification denoting a busy medium-sized railway station with significant passenger usage and facilities.
  • D. DfT category D
    DfT category D is a UK Department for Transport vehicle classification band used to group certain types of vehicles by shared regulatory or operational characteristics.
  • E. DfT category E
    DfT category E is a classification used by the UK Department for Transport for small, typically unstaffed or lightly staffed local railway stations with relatively low passenger usage.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f680cec8190836a5ec841dee224 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d01a23c819095cf75b7d5a801a9 completed May 9, 2026, 12:48 p.m.
Created at: April 10, 2026, 3:33 a.m.