Triple

T15046159
Position Surface form Disambiguated ID Type / Status
Subject Earlestown railway station E379229 entity
Predicate hasStationCode P1289 FINISHED
Object ERL
ERL is the National Rail station code for Earlestown railway station in Merseyside, England.
 E1133528 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: ERL | Statement: [Earlestown railway station, hasStationCode, ERL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ERL
Context triple: [Earlestown railway station, hasStationCode, ERL]
  • A. ERL
    ERL is a research facility focused on studying and developing technologies for the exploration, monitoring, and management of Earth's natural resources.
  • B. ERLC
    ERLC is the public policy and ethics arm of the Southern Baptist Convention, focusing on religious liberty, moral issues, and cultural engagement from an evangelical Christian perspective.
  • C. ER3
    ER3 is the IATA aircraft type code used to designate the Embraer ERJ 135 regional jet.
  • D. ERZ
    ERZ is the vehicle registration code for the Erzgebirgskreis district in the Free State of Saxony, Germany.
  • E. ERZ
    ERZ is the IATA airport code for Erzurum Airport, a public airport serving the city of Erzurum in eastern Turkey.
  • 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: ERL
Triple: [Earlestown railway station, hasStationCode, ERL]
Generated description
ERL is the National Rail station code for Earlestown railway station in Merseyside, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ERL
Target entity description: ERL is the National Rail station code for Earlestown railway station in Merseyside, England.
  • A. ERL
    ERL is a research facility focused on studying and developing technologies for the exploration, monitoring, and management of Earth's natural resources.
  • B. ERLC
    ERLC is the public policy and ethics arm of the Southern Baptist Convention, focusing on religious liberty, moral issues, and cultural engagement from an evangelical Christian perspective.
  • C. ER3
    ER3 is the IATA aircraft type code used to designate the Embraer ERJ 135 regional jet.
  • D. ERZ
    ERZ is the vehicle registration code for the Erzgebirgskreis district in the Free State of Saxony, Germany.
  • E. ERZ
    ERZ is the IATA airport code for Erzurum Airport, a public airport serving the city of Erzurum in eastern Turkey.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded830c3c08190a87b81abbbb75377 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9de73614819098b7a88624407d0e completed May 9, 2026, 2:37 a.m.
NEDg Description generation batch_69fe9f49b1108190a453ef3805006e6c completed May 9, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_69fe9fb79bd08190b22f92df751d0e58 completed May 9, 2026, 2:45 a.m.
Created at: April 10, 2026, 3 a.m.