Triple

T4308224
Position Surface form Disambiguated ID Type / Status
Subject Southend Airport railway station E94009 entity
Predicate hasStationCode P1289 FINISHED
Object SIA
SIA is the National Rail station code for Southend Airport railway station in Essex, England.
 E429255 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: SIA | Statement: [Southend Airport railway station, hasStationCode, SIA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SIA
Context triple: [Southend Airport railway station, hasStationCode, SIA]
  • A. SIA
    SIA is the ICAO airline designator used to identify Singapore Airlines in international aviation operations and communications.
  • B. Sia
    Sia is an Australian singer-songwriter and pop artist known for her powerful vocals, emotive songwriting, and distinctive visual style featuring face-obscuring wigs.
  • C. SIAC
    SIAC is a collegiate athletic conference in the United States composed primarily of historically Black colleges and universities competing in NCAA Division II sports.
  • D. SAM
    SAM is the commonly used abbreviation for the South Australian Museum, a major natural history and cultural institution located in Adelaide, Australia.
  • E. SAM
    SAM is an analytical laboratory aboard NASA's Curiosity rover that studies Martian rocks, soil, and atmosphere to determine their chemical and organic composition.
  • 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: SIA
Triple: [Southend Airport railway station, hasStationCode, SIA]
Generated description
SIA is the National Rail station code for Southend Airport railway station in Essex, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SIA
Target entity description: SIA is the National Rail station code for Southend Airport railway station in Essex, England.
  • A. SIA
    SIA is the ICAO airline designator used to identify Singapore Airlines in international aviation operations and communications.
  • B. Sia
    Sia is an Australian singer-songwriter and pop artist known for her powerful vocals, emotive songwriting, and distinctive visual style featuring face-obscuring wigs.
  • C. SIAC
    SIAC is a collegiate athletic conference in the United States composed primarily of historically Black colleges and universities competing in NCAA Division II sports.
  • D. SAM
    SAM is the commonly used abbreviation for the South Australian Museum, a major natural history and cultural institution located in Adelaide, Australia.
  • E. SAM
    SAM is an analytical laboratory aboard NASA's Curiosity rover that studies Martian rocks, soil, and atmosphere to determine their chemical and organic composition.
  • 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_69b3451886588190a3dd1305ea7c58dc completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b350d2af088190ad7cb035d6e0f8c2 completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c756809c8190af90c91ec7883e55 completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c804f3f881908dd2d020d07c4859 completed March 14, 2026, 8:41 p.m.
NED2 Entity disambiguation (via description) batch_69b5c84e48b8819080571f995d8baf13 completed March 14, 2026, 8:42 p.m.
Created at: March 12, 2026, 11:11 p.m.