Triple

T13731335
Position Surface form Disambiguated ID Type / Status
Subject Settle railway station E329806 entity
Predicate hasStationCode P1289 FINISHED
Object SET
SET is the National Rail station code for Settle railway station in North Yorkshire, England.
 E1056711 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: SET | Statement: [Settle railway station, hasStationCode, SET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SET
Context triple: [Settle railway station, hasStationCode, SET]
  • A. SET
    SET is an open-source penetration testing framework focused on social engineering attacks, commonly used by security professionals to simulate and assess human-targeted vulnerabilities.
  • B. SET
    SET is the Stock Exchange of Thailand, the primary securities exchange for trading stocks and other financial instruments in Thailand.
  • C. Set
    Set is an ancient Egyptian god associated primarily with chaos, storms, and disorder, often depicted as the adversary of his brother Osiris and the rival of Horus.
  • D. SETS
    SETS is the London Stock Exchange’s central electronic order book system used for automated trading of the most liquid UK securities.
  • E. SETSqx
    SETSqx is a hybrid electronic trading service on the London Stock Exchange that combines periodic auctions with continuous quote-driven market making for less liquid securities.
  • 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: SET
Triple: [Settle railway station, hasStationCode, SET]
Generated description
SET is the National Rail station code for Settle railway station in North Yorkshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SET
Target entity description: SET is the National Rail station code for Settle railway station in North Yorkshire, England.
  • A. SET
    SET is an open-source penetration testing framework focused on social engineering attacks, commonly used by security professionals to simulate and assess human-targeted vulnerabilities.
  • B. SET
    SET is the Stock Exchange of Thailand, the primary securities exchange for trading stocks and other financial instruments in Thailand.
  • C. Set
    Set is an ancient Egyptian god associated primarily with chaos, storms, and disorder, often depicted as the adversary of his brother Osiris and the rival of Horus.
  • D. SETS
    SETS is the London Stock Exchange’s central electronic order book system used for automated trading of the most liquid UK securities.
  • E. SETSqx
    SETSqx is a hybrid electronic trading service on the London Stock Exchange that combines periodic auctions with continuous quote-driven market making for less liquid securities.
  • 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_69d80772315881908f980cae40d91664 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69de01f92b588190be97ec4564dddd59 completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f79d65062c819086a5f7a7ebc45412 completed May 3, 2026, 7:09 p.m.
NEDg Description generation batch_69f79e1a90408190936cb71e567e10aa completed May 3, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_69f79ee74ea48190a4c753b12bb9190e completed May 3, 2026, 7:15 p.m.
Created at: April 9, 2026, 9:55 p.m.