Triple

T14307388
Position Surface form Disambiguated ID Type / Status
Subject Casula railway station E354732 entity
Predicate hasStationCode P1289 FINISHED
Object CSA
CSA is the station code for Casula railway station, a suburban train station in Sydney, New South Wales, Australia.
E1090975 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: CSA | Statement: [Casula railway station, hasStationCode, CSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CSA
Context triple: [Casula railway station, hasStationCode, CSA]
  • A. CSA
    CSA is the common abbreviation for the Controlled Substances Act, the primary U.S. federal law regulating the manufacture, distribution, and use of certain drugs and chemicals.
  • B. CSA
    CSA is the College Squash Association, the governing body that oversees intercollegiate squash competition and regulations in the United States.
  • C. CSA
    CSA is the abbreviation for the Connectivity Standards Alliance, an industry consortium that develops and promotes open standards for smart home and Internet of Things devices, including the Matter protocol.
  • D. CSA
    CSA is the commonly used abbreviation for the Saginaw–Midland–Bay City Combined Statistical Area in Michigan, United States.
  • E. CSA
    CSA is an abbreviation that commonly stands for the Combined Statistical Area encompassing the Fayetteville, Lumberton, and Laurinburg regions.
  • 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: CSA
Triple: [Casula railway station, hasStationCode, CSA]
Generated description
CSA is the station code for Casula railway station, a suburban train station in Sydney, New South Wales, Australia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CSA
Target entity description: CSA is the station code for Casula railway station, a suburban train station in Sydney, New South Wales, Australia.
  • A. CSA
    CSA is an abbreviation that commonly stands for the Combined Statistical Area encompassing the Fayetteville, Lumberton, and Laurinburg regions.
  • B. CSA
    CSA is the commonly used abbreviation for the Canadian Screen Award, an annual honor recognizing excellence in Canadian film, television, and digital media.
  • C. CSA
    CSA is the commonly used abbreviation for France’s former audiovisual regulatory authority, the Conseil supérieur de l’audiovisuel.
  • D. CSA
    CSA is the umbrella organization of Canada’s provincial and territorial securities regulators that coordinates and harmonizes regulation of the Canadian capital markets.
  • E. CSA
    CSA is the Canadian Space Agency, the national organization responsible for Canada’s civil space program and space research activities.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de85b156b0819083f2bd319deed1b6 completed April 14, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d2c32648190bc8bb26d57df57f5 completed May 8, 2026, 1:32 a.m.
NEDg Description generation batch_69fd3e3d3e2c81909945253c26e19cee completed May 8, 2026, 1:37 a.m.
NED2 Entity disambiguation (via description) batch_69fd3ebe4f008190aec72ed7e23c4cd4 completed May 8, 2026, 1:39 a.m.
Created at: April 10, 2026, 1:12 a.m.