Triple

T16458218
Position Surface form Disambiguated ID Type / Status
Subject Seaforth and Litherland railway station E399735 entity
Predicate hasStationCode P1289 FINISHED
Object SFL
SFL is the National Rail station code for Seaforth and Litherland railway station in Merseyside, England.
 E1214717 NE FINISHED

How this triple was built (4 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: SFL | Statement: [Seaforth and Litherland railway station, hasStationCode, SFL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SFL
Context triple: [Seaforth and Litherland railway station, hasStationCode, SFL]
  • A. SFL
    SFL is the commonly used abbreviation for the Swiss Super League, the top tier of professional football in Switzerland.
  • B. SFL
    SFL is the commonly used abbreviation for the Scottish Football League, the former governing body for professional league football in Scotland.
  • C. SLFL
    SLFL is the commonly used abbreviation for the Scottish Lowland Football League, a senior football league in the fifth tier of the Scottish football pyramid.
  • D. SLF
    SLF is the Shuttle Landing Facility at NASA’s Kennedy Space Center, a specialized runway complex built for landing Space Shuttle orbiters and other aerospace vehicles.
  • E. SFLC
    SFLC is a legal organization that provides pro bono counsel and advocacy to protect and advance free and open-source software.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SFL
Triple: [Seaforth and Litherland railway station, hasStationCode, SFL]
Generated description
SFL is the National Rail station code for Seaforth and Litherland railway station in Merseyside, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SFL
Target entity description: SFL is the National Rail station code for Seaforth and Litherland railway station in Merseyside, England.
  • A. SFL
    SFL is the commonly used abbreviation for the Scottish Football League, the former governing body for professional league football in Scotland.
  • B. SFL
    SFL is the commonly used abbreviation for the Swiss Super League, the top tier of professional football in Switzerland.
  • C. SLFL
    SLFL is the commonly used abbreviation for the Scottish Lowland Football League, a senior football league in the fifth tier of the Scottish football pyramid.
  • D. SLF
    SLF is the Shuttle Landing Facility at NASA’s Kennedy Space Center, a specialized runway complex built for landing Space Shuttle orbiters and other aerospace vehicles.
  • E. SFLC
    SFLC is a legal organization that provides pro bono counsel and advocacy to protect and advance free and open-source software.
  • F. None of above. chosen

Provenance (5 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d7ef5cc819084cfeb1a3e39d3cc completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f51d93081909ede0adcf8e604d4 completed May 10, 2026, 9:26 a.m.
NEDg Description generation batch_6a004fb5c28c81909da3d7b9b5c2be72 completed May 10, 2026, 9:28 a.m.
NED2 Entity disambiguation (via description) batch_6a00504d177c8190b4a4b4202d0167bb completed May 10, 2026, 9:30 a.m.
Created at: April 10, 2026, 5:10 a.m.