Triple

T7317963
Position Surface form Disambiguated ID Type / Status
Subject Mernda line E168461 entity
Predicate hasStation P35 FINISHED
Object Lalor
Lalor is a suburban railway station in Melbourne, Australia, serving the local community on the metropolitan train network.
 E656861 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: Lalor | Statement: [Mernda line, hasStation, Lalor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lalor
Context triple: [Mernda line, hasStation, Lalor]
  • A. Sculthorpe
    Sculthorpe is a small village in Norfolk, England, known for its rural character and proximity to the market town of Fakenham.
  • B. Willunga
    Willunga is a historic township in South Australia known for its vineyards and role as a subregion within the renowned McLaren Vale wine-producing area.
  • C. Loxton
    Loxton is a rural town in South Australia's Riverland region, known for its irrigated agriculture, particularly citrus and grape production, and its location along the Murray River.
  • D. Anglesea
    Anglesea is a coastal town in Victoria, Australia, known for its beaches, surf breaks, and scenic bushland along the state’s southwest coast.
  • E. Sholto
    Sholto is a masculine given name of Scottish origin, historically associated with figures such as military leaders and nobles.
  • 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: Lalor
Triple: [Mernda line, hasStation, Lalor]
Generated description
Lalor is a suburban railway station in Melbourne, Australia, serving the local community on the metropolitan train network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lalor
Target entity description: Lalor is a suburban railway station in Melbourne, Australia, serving the local community on the metropolitan train network.
  • A. Sculthorpe
    Sculthorpe is a small village in Norfolk, England, known for its rural character and proximity to the market town of Fakenham.
  • B. Willunga
    Willunga is a historic township in South Australia known for its vineyards and role as a subregion within the renowned McLaren Vale wine-producing area.
  • C. Loxton
    Loxton is a rural town in South Australia's Riverland region, known for its irrigated agriculture, particularly citrus and grape production, and its location along the Murray River.
  • D. Anglesea
    Anglesea is a coastal town in Victoria, Australia, known for its beaches, surf breaks, and scenic bushland along the state’s southwest coast.
  • E. Sholto
    Sholto is a masculine given name of Scottish origin, historically associated with figures such as military leaders and nobles.
  • 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_69c68a5251508190ad68df4151cfeb04 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6ef178b3081908cd0c62466069741 completed March 27, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eef847948190a0f2066008f63efd completed March 28, 2026, 3:08 p.m.
NEDg Description generation batch_69c7ef6cf4208190b6242aaea1e20b8e completed March 28, 2026, 3:10 p.m.
NED2 Entity disambiguation (via description) batch_69c7f01543e8819082bf2dfd49d8fb28 completed March 28, 2026, 3:13 p.m.
Created at: March 27, 2026, 3:02 p.m.